S. Madenda | Gunadarma University (original) (raw)

Papers by S. Madenda

Research paper thumbnail of Identification of mangrove tree species using deep learning method

International Journal of Advances in Applied Sciences

Artificial intelligence can help classify plants to make identification easier for everyone. This... more Artificial intelligence can help classify plants to make identification easier for everyone. This technology can be used to classify mangrove trees. The degradation of mangrove forests has resulted in a 20% loss of biodiversity, an 80% loss of microbial decomposers, reduced C-organic soil, and fish spawning grounds, resulting in estimated losses in the ecological and economic fields for up to IDR 39 billion. The identification of different mangrove species is the first step in ensuring the preservation of these forests. Therefore, this research aimed to develop algorithms and a convolutional neural network (CNN) architecture to classify mangrove tree species with the highest possible accuracy using Python software. The architecture selection for this model includes a batch size of 32, an input image size of 128x128 pixels, four classes, four convolution layers, four rectified linear unit (ReLU) layers, 2x2 max-pooling, and two fully connected layers (FCL). The finding showed that th...

Research paper thumbnail of Identification of mangrove tree species using deep learning method

International Journal of Advances in Applied Sciences

Artificial intelligence can help classify plants to make identification easier for everyone. This... more Artificial intelligence can help classify plants to make identification easier for everyone. This technology can be used to classify mangrove trees. The degradation of mangrove forests has resulted in a 20% loss of biodiversity, an 80% loss of microbial decomposers, reduced C-organic soil, and fish spawning grounds, resulting in estimated losses in the ecological and economic fields for up to IDR 39 billion. The identification of different mangrove species is the first step in ensuring the preservation of these forests. Therefore, this research aimed to develop algorithms and a convolutional neural network (CNN) architecture to classify mangrove tree species with the highest possible accuracy using Python software. The architecture selection for this model includes a batch size of 32, an input image size of 128x128 pixels, four classes, four convolution layers, four rectified linear unit (ReLU) layers, 2x2 max-pooling, and two fully connected layers (FCL). The finding showed that th...

Research paper thumbnail of Benign and malignant breast tumors classification based on texture analysis and backpropagation neural network

Computer Optics, 2021

Breast cancer is a leading cause of death in women due to cancer. According to WHO in 2018, it is... more Breast cancer is a leading cause of death in women due to cancer. According to WHO in 2018, it is estimated that 627.000 women died from breast cancer, that is approximately 15 % of all cancer deaths among women [3]. Early detection is a very important factor to reduce mortality by 25-30 %. Mammography is the most commonly used technique in detecting breast cancer using a low-dose X-ray system in the examination of breast tissue that can reduce false positives. A Computer-Aided Detection (CAD) system has been developed to effectively assist radiologists in detecting masses on mammograms that indicate the presence of breast tumors. The type of abnormality in mammogram images can be seen from the presence of microcalcifications and the presence of mass lesions. In this research, a new approach was developed to improve the performance of CAD System for classifying benign and malignant tumors. Areas suspected of being masses (RoI) in mammogram images were detected using an adaptive thre...

Research paper thumbnail of Reconstruction 4D of Blood Flow MR Imaging on Abdominal Aortic Aneurysms with Thrombus Signal

Cine MRI (amplitude image and phase contrast image) has been used to represent the blood flow vel... more Cine MRI (amplitude image and phase contrast image) has been used to represent the blood flow velocity on the aortic aneurysm. Acquisition of images taken perpendicular to the abdominal aorta is done in free breathing and breath hold at the specified location as needed. Active Contour method or Snake (Deformable Model) has been used to perform automatic contour on amplitude image to detect the surface of the aorta and obtain the required parameter values. Furthermore, image reconstruction is performed on the object's surface from several slices of image segmentation that results with Scalar Volume Data technique (isosurface) in order to obtain the value of blood flow volume. The method has been developed and can represent animation of aortic aneurysm with blood flow velocity on each category of thrombus.

Research paper thumbnail of Adaptive color space model based on dominant colors for image and video compression performance improvement

Computer Optics, 2021

This paper describes the use of some color spaces in JPEG image compression algorithm and their i... more This paper describes the use of some color spaces in JPEG image compression algorithm and their impact in terms of image quality and compression ratio, and then proposes adaptive color space models (ACSM) to improve the performance of lossy image compression algorithm. The proposed ACSM consists of, dominant color analysis algorithm and YCoCg color space family. The YCoCg color space family is composed of three color spaces, which are YCcCr, YCpCg and YCyCb. The dominant colors analysis algorithm is developed which enables to automatically select one of the three color space models based on the suitability of the dominant colors contained in an image. The experimental results using sixty test images, which have varying colors, shapes and textures, show that the proposed adaptive color space model provides improved performance of 3 % to 10 % better than YCbCr, YDbDr, YCoCg and YCgCo-R color spaces family. In addition, the YCoCg color space family is a discrete transformation so its d...

Research paper thumbnail of Identification of hand motion using background subtraction method and extraction of image binary with backpropagation neural network on skeleton model

Journal of Physics: Conference Series, 2018

Capturing and recording motion in human is mostly done with the aim for sports, health, animation... more Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural network. This purpose to produce, find similarity movement. The acquisition process using 8 MP resolution camera MP4 format, duration 48 seconds, 30frame/rate. video extracted produced 1444 pieces and results hand motion identification process. Phase of image processing performed is segmentation process, feature extraction, identification. Segmentation using bakground subtraction, extracted feature basically used to distinguish between one object to another object. Feature extraction performed by using motion based morfology analysis based on 7 invariant moment producing four different classes motion: no object, hand down, hand-to-side and hands-up. Identification process used to recognize of hand movement using seven inputs. Testing and training with a variety of para...

Research paper thumbnail of Tajweed Segmentation Using Pattern Recognition, Extraction and SURF descriptor Algorithms

IOP Conference Series: Materials Science and Engineering, 2020

This paper proposes a method of detection and recognition algorithms and recitation of the Qur’an... more This paper proposes a method of detection and recognition algorithms and recitation of the Qur’an. The methods and algorithms are packaged into a software system application to allow a person to learn recitation and how pronunciation is good and right and real-time. Any recitation of the Qur’an written in a different color of the letters and punctuation instead of recitation and tajweed each have different shapes. Variable color is used as a reference for the segmentation process forms of recitation and SURF algorithm used for feature extraction process forms. Feature any form of recitation is stored in the data base (knowledge base) accompanied by explanatory text recitation of data and audio pronunciation files. In the process of recognition when the user enters a query tajweed image, Euclidian distance is used to measure the similarity between the query and the shape feature tajweed recitation shape features that exist in the database.

Research paper thumbnail of Detection of Proximal Caries at The Molar Teeth Using Edge Enhancement Algorithm

International Journal of Electrical and Computer Engineering (IJECE), 2018

Panoramic X-Ray produces the most common oral digital radiographic image that it used in dentistr... more Panoramic X-Ray produces the most common oral digital radiographic image that it used in dentistry practice. The image can further improve accuracy compared to analog one. This study aims to establish proximal caries edge on enhancement images so they can be easily recognized. The images were obtained from the Department of Radiology, General Hospital of M. Djamil Padang Indonesia. Total file of images to be tested were 101. Firstly, the images are analyzed by dentists who practiced at Segment Padang Hospital Indonesia. They concluded that there is proximal caries in 30 molar teeth. Furthermore, the images were processed using Matlab software with the following steps, i.e. cropping, enhancement, edge detection, and edge enhancement. The accuracy rate of detection of edge enhancement images being compared with that of dentist analysis was 73.3%. In the edge enhancement images proximal caries edge can be found conclusively in 22 teeth and dubiously in eight teeth. The results of this study convinced that edge enhancement images can be recommended to assist dentists in detecting proximal caries.

Research paper thumbnail of Hybrids Otsu method, Feature region and Mathematical Morphology for Calculating Volume Hemorrhage Brain on CT-Scan Image and 3D Reconstruction

TELKOMNIKA (Telecommunication Computing Electronics and Control), 2017

Hemorrhage in the brain is a process of pathological culture from the tissues of the brain with t... more Hemorrhage in the brain is a process of pathological culture from the tissues of the brain with the strength of the external mechanical, which cause physical disorders, cognitive function, and psychosocial support. Brain bleeding can cause was bruised, network torn, bleeding and brain damage or death.Segmentation techniques can be done with the Scanner computed tomography images (CT-scan) to detect the abnormalities or bleeding of the brain which occurs in the brain. This research describes the taking of an area of the brain bleeding on each image slice CT-scan and reconstruction 3D, to visualize the image of the 3D and calculate the volume of the brain bleeding. Extraction of bleeding area of the brain is based on a hybrids of Otsu algorithm, morphological features algorithm algorithm and an area of bleeding. For the reconstruction of 3D area on the area of bleeding from a slice 2D is done by using a linear interpolation approach.

Research paper thumbnail of Dimensionality Reduction of Laplacian Embedding for 3D Mesh Reconstruction

Journal of Physics: Conference Series, 2016

Laplacian eigenbases are the important thing that we have to process from 3D mesh information. Th... more Laplacian eigenbases are the important thing that we have to process from 3D mesh information. The information of geometric 3D mesh are include vertices locations and the connectivity of graph. Due to spectral analysis, geometric 3D mesh for large and sparse graphs with thousands of vertices is not practical to compute all the eigenvalues and eigenvector. Because of that, in this paper we discuss how to build 3D mesh reconstruction by reducing dimensionality on null eigenvalue but retain the corresponding eigenvector of Laplacian Embedding to simplify mesh processing. The result of reducing information should have to retained the connectivity of graph. The advantages of dimensionality reduction is for computational eficiency and problem simplification. Laplacian eigenbases is the point of dimensionality reduction for 3D mesh reconstruction. In this paper, we show how to reconstruct geometric 3D mesh after approximation step of 3D mesh by dimensionality reduction. Dimensionality reduction shown by Laplacian Embedding matrix. Furthermore, the effectiveness of 3D mesh reconstruction method will evaluated by geometric error, differential error, and final error. Numerical approximation error of our result are small and low complexity of computational.

Research paper thumbnail of Identification of the Proximal Caries of Dental X-Ray Image with Multiple Morphology Gradient Method

International Journal on Advanced Science, Engineering and Information Technology, 2016

This study aims to perform the sharpening of the dental x-ray image in the form of a panoramic de... more This study aims to perform the sharpening of the dental x-ray image in the form of a panoramic dental x-ray. The method used in this study was segmentation morphology consisting of the dilation, erosion and gradient process. This study also developed a process of morphology gradient of subtracting morphology dilation results with the results of morphology erosion dilation in iterating basis. The results achieved indicate that the image enhancement process in each iteration stage can display caries objects clearly, making it easier to identify proximal caries. In this study have been compiled a looping morphology gradient algorithm which is called multiple morphology gradient.

Research paper thumbnail of Comparison of Neural Network Algorithms to Determine the Range of Motion Using Skeleton Models

International journal of simulation: systems, science & technology, 2019

We have the main characteristics of moving as walking, running, sitting, dancing, eating, drinkin... more We have the main characteristics of moving as walking, running, sitting, dancing, eating, drinking and other activities. The range-of-motion, ROM, is the maximum number of movements that can occur in the sagittal, frontal, and transverse type and consists of flexion, extension, abduction, adduction, hyperextension and others. Decreased ROM can be the result of injury and the aging process and can lead to undesirable motion patterns. Feature extraction in motion analysis involve calculating a number of characteristic values independent of the size to produce the appropriate motion identification using the best method or algorithm during processing. Based on the data types obtained from the process of extracting properties collected using moment invariance, the results of identification based on ROM standard gave an accuracy of 98% using Back propagation Neural Network, 94% using Radial Basis Function Neural Network and 36% using K Means Clustering.

Research paper thumbnail of Wood Texture Features Extraction by Using GLCM Combined With Various Edge Detection Methods

Journal of Physics: Conference Series, 2016

An image forming specific texture can be distinguished manually through the eye. However, sometim... more An image forming specific texture can be distinguished manually through the eye. However, sometimes it is difficult to do if the texture owned quite similar. Wood is a natural material that forms a unique texture. Experts can distinguish the quality of wood based texture observed in certain parts of the wood. In this study, it has been extracted texture features of the wood image that can be used to identify the characteristics of wood digitally by computer. Feature extraction carried out using Gray Level Co-occurrence Matrices (GLCM) built on an image from several edge detection methods applied to wood image. Edge detection methods used include Roberts, Sobel, Prewitt, Canny and Laplacian of Gaussian. The image of wood taken in LE2i laboratory, Universite de Bourgogne from the wood sample in France that grouped by their quality by experts and divided into four types of quality. Obtained a statistic that illustrates the distribution of texture features values of each wood type which compared according to the edge operator that is used and selection of specified GLCM parameters.

Research paper thumbnail of New Concept of Universal Binary Multiplication and Its Implementation on FPGA

Journal of Southwest Jiaotong University

This paper proposes the new improvements of signed binary multiplication equation, signed multipl... more This paper proposes the new improvements of signed binary multiplication equation, signed multiplier, and universal multiplier. The proposed multipliers have low complexity algorithms and are easy to implement into software and hardware. Both signed, and universal multipliers are embedded into FPGA by optimizing the use of LUTs (6-LUT and 5-LUT), carry chain Carry4, and fast carry logics: MUXCYs and XORCYs.Each one is implemented as a serial-parallel multiplier and parallel multiplier. The signed multiplier executes four types of multiplication, i.e., between two operands that each one can be a signed positive (SPN) or signed negative numbers (SNN). The universal multiplier can handle all (nine) types of multiplication, where each operand can be as unsigned(USN), signed positive, and signed negative numbers. For 8x8 bits, signed serial-parallel and signed parallel multipliers occupy19 LUTs and 58 LUTs with a logic time delay of 0.769 ns and 3.600 ns. Besides, for 8x8 bits, serial-pa...

Research paper thumbnail of Cropping Method on Grayscale Images for Periapical Radiographs of Human Teeth

IOP Conference Series: Materials Science and Engineering

Research paper thumbnail of Software Based Programmable IGBT IPM Dead-Time Insertion Module Using 16-bit Micro Controller for BLDC Motor Control Application with 3-Phase Sinusoidal and Trapezoidal Drive

Computer and Information Science

Motor control application, especially for medium to high power implementation, will benefit the m... more Motor control application, especially for medium to high power implementation, will benefit the most with the compactness and robustness of an Integrated Power Module of Insulated Gate Bipolar Transistor also known as IGBT IPM. Nevertheless, implementation motor control with a general purpose micro-processor without any advance timer functionality with IGBT IPM will be challenged by the Dead-Time switching requirement in its power switching implementation. Further, a combined sinusoidal and trapezoidal drive of a motor control is also believed will provides a better control performance in term of lower torque ripple and higher motor top speed. This paper proposed a low-cost alternative to address the requirement by implementing a software based dead time functionality using the low cost 16-bit micro controller board with capability of serving up sinusoidal drive as well as trapezoidal drive for motor control application.

Research paper thumbnail of Retinal Blood Vessel Extraction using Wavelet Decomposition

International Journal of Advanced Computer Science and Applications

One important part of the eye that is critical for processing visual information before it is sen... more One important part of the eye that is critical for processing visual information before it is sent through the optic nerve to the visual cortex is the retina. The retina of each individual has its own uniqueness that can be used as a characteristic feature in identifying, verifying, and authenticating. The traditional authentication process has various weaknesses such as forgetting the PIN code or losing the ID card used for obtaining system authentication. The results of extracted retinal blood vessels can be used as a feature in the formation of an individual identification system. In the imaging using a fundus camera, the retina's blood vessel has distinguishing shape and number of candidates from one human retina to another. In this research, researchers will develop an algorithm for extracting the retinal fundus image's blood vessels. The feature extraction is done by taking the fundus image feature which is the blood vessel as one of the unique characteristics in forming an individual identification system. The number of blood vessel candidates will then be calculated from the extracted blood vessel result. This research uses wavelet function by looking at the very complex texture of blood vessels using the approximation coefficient. The direction detail coefficient on the wavelet is also used to perform the extraction of retinal blood vessels where the structure of the retinal blood vessels in the fundus image is in all directions. The results of these blood vessel candidates will be used in further research to formulate a biometric system that is formed by unique features in the retinal fundus image which will be used to identify individuals using body traits.

Research paper thumbnail of Feature Extraction Optimization with Combination 2D-Discrete Wavelet Transform and Gray Level Co-Occurrence Matrix for Classifying Normal and Abnormal Breast Tumors

Modern Applied Science

Breast cancer is one of the leading causes of death worldwide among women. According to GLOBOCAN ... more Breast cancer is one of the leading causes of death worldwide among women. According to GLOBOCAN Data, the International Agency for Research on Cancer (IARC), in 2012 there were 14.067.894 new cases of cancer and 8.201.575 deaths from cancer worldwide (Kementerian Kesehatan Republik Indonesia [KemenkesRI], 2015). Mammography is the most common and effective technique for detecting breast tumors. However, mammograms have poor image quality with low contrast. A Computer-Aided Detection (CAD) system has been developed to help radiologists effectively detect lesions on mammograms that indicate the presence of breast tumor. The feature extraction method in the CAD system is an important part of getting high accuracy results in classifying normal and abnormal breast tumors. By using the combination of 2D-Discrete wavelet transform and Gray-Level Co-Occurrence Matrix (GLCM) obtained an accuracy value of 100% on MIAS and UDIAT Database in classifying the presence of masses in the mammogram ...

Research paper thumbnail of Measurement Range of Motion to Position Straight Leg Raise Based Camera RGB-Depth

DEStech Transactions on Environment, Energy and Earth Science

The camera device based color camera (RGB) and camera depth (Depth) that can detect and track the... more The camera device based color camera (RGB) and camera depth (Depth) that can detect and track the movement of the human skeleton called Kinect. Kinect can process depth data that can function both in a state of both light and dark lighting. In general, Kinect recognize and detect the user and track user joints in a standing or sitting pose. In this study, Kinect is able to track foot skeleton in a lying position with Straight Leg Raise (SLR) in real time and measurement of Range Of Motion. Methods of image aquisition, calibration pose, depth image to feature extraction legs form an angle ROM. Results of this ROM can be used for various purposes, one of them among others to help patients in the physiotherapy and detect the state of spinal pain.

Research paper thumbnail of Efficient Implementation of Mean, Variance and Skewness Statistic Formula for Image Processing Using FPGA Device

Bulletin of Electrical Engineering and Informatics

Processing statistic formula in image processing and accessing data from memory is easy in softwa... more Processing statistic formula in image processing and accessing data from memory is easy in software, the other hand for hardware implementation is more dificult considering a lot of constraint. This article proposes an implementation of optimum mean, variance and skewness formula in FGPA Device. The proposed circuit design for all formulas only need three additions component (in three accumulators) and two divisions using two shift-right-registers, two subtractors, one adder and six multipliers. For 8x8 image size need 64 clock cycles to finish the mean, variance and skewness calculations, comparing other approach that need more than 1024 additions component without skewness calculation. Implementation into FPGA needs 68 slices of flip-flops and 121 of 4 input LUTs.

Research paper thumbnail of Identification of mangrove tree species using deep learning method

International Journal of Advances in Applied Sciences

Artificial intelligence can help classify plants to make identification easier for everyone. This... more Artificial intelligence can help classify plants to make identification easier for everyone. This technology can be used to classify mangrove trees. The degradation of mangrove forests has resulted in a 20% loss of biodiversity, an 80% loss of microbial decomposers, reduced C-organic soil, and fish spawning grounds, resulting in estimated losses in the ecological and economic fields for up to IDR 39 billion. The identification of different mangrove species is the first step in ensuring the preservation of these forests. Therefore, this research aimed to develop algorithms and a convolutional neural network (CNN) architecture to classify mangrove tree species with the highest possible accuracy using Python software. The architecture selection for this model includes a batch size of 32, an input image size of 128x128 pixels, four classes, four convolution layers, four rectified linear unit (ReLU) layers, 2x2 max-pooling, and two fully connected layers (FCL). The finding showed that th...

Research paper thumbnail of Identification of mangrove tree species using deep learning method

International Journal of Advances in Applied Sciences

Artificial intelligence can help classify plants to make identification easier for everyone. This... more Artificial intelligence can help classify plants to make identification easier for everyone. This technology can be used to classify mangrove trees. The degradation of mangrove forests has resulted in a 20% loss of biodiversity, an 80% loss of microbial decomposers, reduced C-organic soil, and fish spawning grounds, resulting in estimated losses in the ecological and economic fields for up to IDR 39 billion. The identification of different mangrove species is the first step in ensuring the preservation of these forests. Therefore, this research aimed to develop algorithms and a convolutional neural network (CNN) architecture to classify mangrove tree species with the highest possible accuracy using Python software. The architecture selection for this model includes a batch size of 32, an input image size of 128x128 pixels, four classes, four convolution layers, four rectified linear unit (ReLU) layers, 2x2 max-pooling, and two fully connected layers (FCL). The finding showed that th...

Research paper thumbnail of Benign and malignant breast tumors classification based on texture analysis and backpropagation neural network

Computer Optics, 2021

Breast cancer is a leading cause of death in women due to cancer. According to WHO in 2018, it is... more Breast cancer is a leading cause of death in women due to cancer. According to WHO in 2018, it is estimated that 627.000 women died from breast cancer, that is approximately 15 % of all cancer deaths among women [3]. Early detection is a very important factor to reduce mortality by 25-30 %. Mammography is the most commonly used technique in detecting breast cancer using a low-dose X-ray system in the examination of breast tissue that can reduce false positives. A Computer-Aided Detection (CAD) system has been developed to effectively assist radiologists in detecting masses on mammograms that indicate the presence of breast tumors. The type of abnormality in mammogram images can be seen from the presence of microcalcifications and the presence of mass lesions. In this research, a new approach was developed to improve the performance of CAD System for classifying benign and malignant tumors. Areas suspected of being masses (RoI) in mammogram images were detected using an adaptive thre...

Research paper thumbnail of Reconstruction 4D of Blood Flow MR Imaging on Abdominal Aortic Aneurysms with Thrombus Signal

Cine MRI (amplitude image and phase contrast image) has been used to represent the blood flow vel... more Cine MRI (amplitude image and phase contrast image) has been used to represent the blood flow velocity on the aortic aneurysm. Acquisition of images taken perpendicular to the abdominal aorta is done in free breathing and breath hold at the specified location as needed. Active Contour method or Snake (Deformable Model) has been used to perform automatic contour on amplitude image to detect the surface of the aorta and obtain the required parameter values. Furthermore, image reconstruction is performed on the object's surface from several slices of image segmentation that results with Scalar Volume Data technique (isosurface) in order to obtain the value of blood flow volume. The method has been developed and can represent animation of aortic aneurysm with blood flow velocity on each category of thrombus.

Research paper thumbnail of Adaptive color space model based on dominant colors for image and video compression performance improvement

Computer Optics, 2021

This paper describes the use of some color spaces in JPEG image compression algorithm and their i... more This paper describes the use of some color spaces in JPEG image compression algorithm and their impact in terms of image quality and compression ratio, and then proposes adaptive color space models (ACSM) to improve the performance of lossy image compression algorithm. The proposed ACSM consists of, dominant color analysis algorithm and YCoCg color space family. The YCoCg color space family is composed of three color spaces, which are YCcCr, YCpCg and YCyCb. The dominant colors analysis algorithm is developed which enables to automatically select one of the three color space models based on the suitability of the dominant colors contained in an image. The experimental results using sixty test images, which have varying colors, shapes and textures, show that the proposed adaptive color space model provides improved performance of 3 % to 10 % better than YCbCr, YDbDr, YCoCg and YCgCo-R color spaces family. In addition, the YCoCg color space family is a discrete transformation so its d...

Research paper thumbnail of Identification of hand motion using background subtraction method and extraction of image binary with backpropagation neural network on skeleton model

Journal of Physics: Conference Series, 2018

Capturing and recording motion in human is mostly done with the aim for sports, health, animation... more Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural network. This purpose to produce, find similarity movement. The acquisition process using 8 MP resolution camera MP4 format, duration 48 seconds, 30frame/rate. video extracted produced 1444 pieces and results hand motion identification process. Phase of image processing performed is segmentation process, feature extraction, identification. Segmentation using bakground subtraction, extracted feature basically used to distinguish between one object to another object. Feature extraction performed by using motion based morfology analysis based on 7 invariant moment producing four different classes motion: no object, hand down, hand-to-side and hands-up. Identification process used to recognize of hand movement using seven inputs. Testing and training with a variety of para...

Research paper thumbnail of Tajweed Segmentation Using Pattern Recognition, Extraction and SURF descriptor Algorithms

IOP Conference Series: Materials Science and Engineering, 2020

This paper proposes a method of detection and recognition algorithms and recitation of the Qur’an... more This paper proposes a method of detection and recognition algorithms and recitation of the Qur’an. The methods and algorithms are packaged into a software system application to allow a person to learn recitation and how pronunciation is good and right and real-time. Any recitation of the Qur’an written in a different color of the letters and punctuation instead of recitation and tajweed each have different shapes. Variable color is used as a reference for the segmentation process forms of recitation and SURF algorithm used for feature extraction process forms. Feature any form of recitation is stored in the data base (knowledge base) accompanied by explanatory text recitation of data and audio pronunciation files. In the process of recognition when the user enters a query tajweed image, Euclidian distance is used to measure the similarity between the query and the shape feature tajweed recitation shape features that exist in the database.

Research paper thumbnail of Detection of Proximal Caries at The Molar Teeth Using Edge Enhancement Algorithm

International Journal of Electrical and Computer Engineering (IJECE), 2018

Panoramic X-Ray produces the most common oral digital radiographic image that it used in dentistr... more Panoramic X-Ray produces the most common oral digital radiographic image that it used in dentistry practice. The image can further improve accuracy compared to analog one. This study aims to establish proximal caries edge on enhancement images so they can be easily recognized. The images were obtained from the Department of Radiology, General Hospital of M. Djamil Padang Indonesia. Total file of images to be tested were 101. Firstly, the images are analyzed by dentists who practiced at Segment Padang Hospital Indonesia. They concluded that there is proximal caries in 30 molar teeth. Furthermore, the images were processed using Matlab software with the following steps, i.e. cropping, enhancement, edge detection, and edge enhancement. The accuracy rate of detection of edge enhancement images being compared with that of dentist analysis was 73.3%. In the edge enhancement images proximal caries edge can be found conclusively in 22 teeth and dubiously in eight teeth. The results of this study convinced that edge enhancement images can be recommended to assist dentists in detecting proximal caries.

Research paper thumbnail of Hybrids Otsu method, Feature region and Mathematical Morphology for Calculating Volume Hemorrhage Brain on CT-Scan Image and 3D Reconstruction

TELKOMNIKA (Telecommunication Computing Electronics and Control), 2017

Hemorrhage in the brain is a process of pathological culture from the tissues of the brain with t... more Hemorrhage in the brain is a process of pathological culture from the tissues of the brain with the strength of the external mechanical, which cause physical disorders, cognitive function, and psychosocial support. Brain bleeding can cause was bruised, network torn, bleeding and brain damage or death.Segmentation techniques can be done with the Scanner computed tomography images (CT-scan) to detect the abnormalities or bleeding of the brain which occurs in the brain. This research describes the taking of an area of the brain bleeding on each image slice CT-scan and reconstruction 3D, to visualize the image of the 3D and calculate the volume of the brain bleeding. Extraction of bleeding area of the brain is based on a hybrids of Otsu algorithm, morphological features algorithm algorithm and an area of bleeding. For the reconstruction of 3D area on the area of bleeding from a slice 2D is done by using a linear interpolation approach.

Research paper thumbnail of Dimensionality Reduction of Laplacian Embedding for 3D Mesh Reconstruction

Journal of Physics: Conference Series, 2016

Laplacian eigenbases are the important thing that we have to process from 3D mesh information. Th... more Laplacian eigenbases are the important thing that we have to process from 3D mesh information. The information of geometric 3D mesh are include vertices locations and the connectivity of graph. Due to spectral analysis, geometric 3D mesh for large and sparse graphs with thousands of vertices is not practical to compute all the eigenvalues and eigenvector. Because of that, in this paper we discuss how to build 3D mesh reconstruction by reducing dimensionality on null eigenvalue but retain the corresponding eigenvector of Laplacian Embedding to simplify mesh processing. The result of reducing information should have to retained the connectivity of graph. The advantages of dimensionality reduction is for computational eficiency and problem simplification. Laplacian eigenbases is the point of dimensionality reduction for 3D mesh reconstruction. In this paper, we show how to reconstruct geometric 3D mesh after approximation step of 3D mesh by dimensionality reduction. Dimensionality reduction shown by Laplacian Embedding matrix. Furthermore, the effectiveness of 3D mesh reconstruction method will evaluated by geometric error, differential error, and final error. Numerical approximation error of our result are small and low complexity of computational.

Research paper thumbnail of Identification of the Proximal Caries of Dental X-Ray Image with Multiple Morphology Gradient Method

International Journal on Advanced Science, Engineering and Information Technology, 2016

This study aims to perform the sharpening of the dental x-ray image in the form of a panoramic de... more This study aims to perform the sharpening of the dental x-ray image in the form of a panoramic dental x-ray. The method used in this study was segmentation morphology consisting of the dilation, erosion and gradient process. This study also developed a process of morphology gradient of subtracting morphology dilation results with the results of morphology erosion dilation in iterating basis. The results achieved indicate that the image enhancement process in each iteration stage can display caries objects clearly, making it easier to identify proximal caries. In this study have been compiled a looping morphology gradient algorithm which is called multiple morphology gradient.

Research paper thumbnail of Comparison of Neural Network Algorithms to Determine the Range of Motion Using Skeleton Models

International journal of simulation: systems, science & technology, 2019

We have the main characteristics of moving as walking, running, sitting, dancing, eating, drinkin... more We have the main characteristics of moving as walking, running, sitting, dancing, eating, drinking and other activities. The range-of-motion, ROM, is the maximum number of movements that can occur in the sagittal, frontal, and transverse type and consists of flexion, extension, abduction, adduction, hyperextension and others. Decreased ROM can be the result of injury and the aging process and can lead to undesirable motion patterns. Feature extraction in motion analysis involve calculating a number of characteristic values independent of the size to produce the appropriate motion identification using the best method or algorithm during processing. Based on the data types obtained from the process of extracting properties collected using moment invariance, the results of identification based on ROM standard gave an accuracy of 98% using Back propagation Neural Network, 94% using Radial Basis Function Neural Network and 36% using K Means Clustering.

Research paper thumbnail of Wood Texture Features Extraction by Using GLCM Combined With Various Edge Detection Methods

Journal of Physics: Conference Series, 2016

An image forming specific texture can be distinguished manually through the eye. However, sometim... more An image forming specific texture can be distinguished manually through the eye. However, sometimes it is difficult to do if the texture owned quite similar. Wood is a natural material that forms a unique texture. Experts can distinguish the quality of wood based texture observed in certain parts of the wood. In this study, it has been extracted texture features of the wood image that can be used to identify the characteristics of wood digitally by computer. Feature extraction carried out using Gray Level Co-occurrence Matrices (GLCM) built on an image from several edge detection methods applied to wood image. Edge detection methods used include Roberts, Sobel, Prewitt, Canny and Laplacian of Gaussian. The image of wood taken in LE2i laboratory, Universite de Bourgogne from the wood sample in France that grouped by their quality by experts and divided into four types of quality. Obtained a statistic that illustrates the distribution of texture features values of each wood type which compared according to the edge operator that is used and selection of specified GLCM parameters.

Research paper thumbnail of New Concept of Universal Binary Multiplication and Its Implementation on FPGA

Journal of Southwest Jiaotong University

This paper proposes the new improvements of signed binary multiplication equation, signed multipl... more This paper proposes the new improvements of signed binary multiplication equation, signed multiplier, and universal multiplier. The proposed multipliers have low complexity algorithms and are easy to implement into software and hardware. Both signed, and universal multipliers are embedded into FPGA by optimizing the use of LUTs (6-LUT and 5-LUT), carry chain Carry4, and fast carry logics: MUXCYs and XORCYs.Each one is implemented as a serial-parallel multiplier and parallel multiplier. The signed multiplier executes four types of multiplication, i.e., between two operands that each one can be a signed positive (SPN) or signed negative numbers (SNN). The universal multiplier can handle all (nine) types of multiplication, where each operand can be as unsigned(USN), signed positive, and signed negative numbers. For 8x8 bits, signed serial-parallel and signed parallel multipliers occupy19 LUTs and 58 LUTs with a logic time delay of 0.769 ns and 3.600 ns. Besides, for 8x8 bits, serial-pa...

Research paper thumbnail of Cropping Method on Grayscale Images for Periapical Radiographs of Human Teeth

IOP Conference Series: Materials Science and Engineering

Research paper thumbnail of Software Based Programmable IGBT IPM Dead-Time Insertion Module Using 16-bit Micro Controller for BLDC Motor Control Application with 3-Phase Sinusoidal and Trapezoidal Drive

Computer and Information Science

Motor control application, especially for medium to high power implementation, will benefit the m... more Motor control application, especially for medium to high power implementation, will benefit the most with the compactness and robustness of an Integrated Power Module of Insulated Gate Bipolar Transistor also known as IGBT IPM. Nevertheless, implementation motor control with a general purpose micro-processor without any advance timer functionality with IGBT IPM will be challenged by the Dead-Time switching requirement in its power switching implementation. Further, a combined sinusoidal and trapezoidal drive of a motor control is also believed will provides a better control performance in term of lower torque ripple and higher motor top speed. This paper proposed a low-cost alternative to address the requirement by implementing a software based dead time functionality using the low cost 16-bit micro controller board with capability of serving up sinusoidal drive as well as trapezoidal drive for motor control application.

Research paper thumbnail of Retinal Blood Vessel Extraction using Wavelet Decomposition

International Journal of Advanced Computer Science and Applications

One important part of the eye that is critical for processing visual information before it is sen... more One important part of the eye that is critical for processing visual information before it is sent through the optic nerve to the visual cortex is the retina. The retina of each individual has its own uniqueness that can be used as a characteristic feature in identifying, verifying, and authenticating. The traditional authentication process has various weaknesses such as forgetting the PIN code or losing the ID card used for obtaining system authentication. The results of extracted retinal blood vessels can be used as a feature in the formation of an individual identification system. In the imaging using a fundus camera, the retina's blood vessel has distinguishing shape and number of candidates from one human retina to another. In this research, researchers will develop an algorithm for extracting the retinal fundus image's blood vessels. The feature extraction is done by taking the fundus image feature which is the blood vessel as one of the unique characteristics in forming an individual identification system. The number of blood vessel candidates will then be calculated from the extracted blood vessel result. This research uses wavelet function by looking at the very complex texture of blood vessels using the approximation coefficient. The direction detail coefficient on the wavelet is also used to perform the extraction of retinal blood vessels where the structure of the retinal blood vessels in the fundus image is in all directions. The results of these blood vessel candidates will be used in further research to formulate a biometric system that is formed by unique features in the retinal fundus image which will be used to identify individuals using body traits.

Research paper thumbnail of Feature Extraction Optimization with Combination 2D-Discrete Wavelet Transform and Gray Level Co-Occurrence Matrix for Classifying Normal and Abnormal Breast Tumors

Modern Applied Science

Breast cancer is one of the leading causes of death worldwide among women. According to GLOBOCAN ... more Breast cancer is one of the leading causes of death worldwide among women. According to GLOBOCAN Data, the International Agency for Research on Cancer (IARC), in 2012 there were 14.067.894 new cases of cancer and 8.201.575 deaths from cancer worldwide (Kementerian Kesehatan Republik Indonesia [KemenkesRI], 2015). Mammography is the most common and effective technique for detecting breast tumors. However, mammograms have poor image quality with low contrast. A Computer-Aided Detection (CAD) system has been developed to help radiologists effectively detect lesions on mammograms that indicate the presence of breast tumor. The feature extraction method in the CAD system is an important part of getting high accuracy results in classifying normal and abnormal breast tumors. By using the combination of 2D-Discrete wavelet transform and Gray-Level Co-Occurrence Matrix (GLCM) obtained an accuracy value of 100% on MIAS and UDIAT Database in classifying the presence of masses in the mammogram ...

Research paper thumbnail of Measurement Range of Motion to Position Straight Leg Raise Based Camera RGB-Depth

DEStech Transactions on Environment, Energy and Earth Science

The camera device based color camera (RGB) and camera depth (Depth) that can detect and track the... more The camera device based color camera (RGB) and camera depth (Depth) that can detect and track the movement of the human skeleton called Kinect. Kinect can process depth data that can function both in a state of both light and dark lighting. In general, Kinect recognize and detect the user and track user joints in a standing or sitting pose. In this study, Kinect is able to track foot skeleton in a lying position with Straight Leg Raise (SLR) in real time and measurement of Range Of Motion. Methods of image aquisition, calibration pose, depth image to feature extraction legs form an angle ROM. Results of this ROM can be used for various purposes, one of them among others to help patients in the physiotherapy and detect the state of spinal pain.

Research paper thumbnail of Efficient Implementation of Mean, Variance and Skewness Statistic Formula for Image Processing Using FPGA Device

Bulletin of Electrical Engineering and Informatics

Processing statistic formula in image processing and accessing data from memory is easy in softwa... more Processing statistic formula in image processing and accessing data from memory is easy in software, the other hand for hardware implementation is more dificult considering a lot of constraint. This article proposes an implementation of optimum mean, variance and skewness formula in FGPA Device. The proposed circuit design for all formulas only need three additions component (in three accumulators) and two divisions using two shift-right-registers, two subtractors, one adder and six multipliers. For 8x8 image size need 64 clock cycles to finish the mean, variance and skewness calculations, comparing other approach that need more than 1024 additions component without skewness calculation. Implementation into FPGA needs 68 slices of flip-flops and 121 of 4 input LUTs.