shanu sharma - Academia.edu (original) (raw)

Papers by shanu sharma

Advancements in Interdisciplinary Research

Proceedings of the Sixth International Conference on Computer and Communication Technology 2015

Nowadays, there are numerous, unstructured and voluminous videos which leads to high collection o... more Nowadays, there are numerous, unstructured and voluminous videos which leads to high collection of data on web. Searching and navigating through these videos for meaningful information is a time consuming task, whereas a good "summarized video" can provides a user determined information about particular video sequence in definite time limits. So, there is great need of extraction of semantic and useful information from videos for various multimedia applications. The video summarization is the novel and promising method of detecting relevant and informative data from videos and also aims to provide effective and efficient storage of relevant information. This technique of summarization leads to abstraction of most representative and relevant scenes from videos and concatenates to display as one successive and uninterrupted video and thus has been powered up the rapidly progressing research domain. In this paper, all latest and enhanced approaches of video shot detection have been discussed and summarized.

Interdisciplinary Innovations and Developments towards Smart and Sustainable Industries

He has 18 years of teaching and research experience. Dr. Kumar has published more than 100 resear... more He has 18 years of teaching and research experience. Dr. Kumar has published more than 100 research articles in journals and conferences of repute; and supervised 5 Ph.D. and approximately 50 M.Tech. Theses. His current research interests include the

U.Porto Journal of Engineering

In recent times, the computer vision community has seen remarkable growth in the field of scene u... more In recent times, the computer vision community has seen remarkable growth in the field of scene understanding. With such a wide prevalence of images, the importance of this field is growing rapidly along with the technologies involved in it. Semantic Segmentation is an important step in scene understanding which requires the assignment of each pixel in an image to a pre-defined class and achieving 100% accuracy is a challenging task, thereby making it an active research topic among researchers. In this paper, an extensive study and review of the existing Deep Learning (DL) based techniques used for Semantic Segmentation is carried out along with a summary of the datasets and evaluation metrics used for it. The study involved the meticulous selection of relevant research papers in the field of interest by search based on several defined keywords. The study begins with a general and broader focus on Semantic Segmentation as a problem and further narrows its focus on existing Deep Lear...

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)

The advancement of multimedia technology has increased the problem of its storage, transmission a... more The advancement of multimedia technology has increased the problem of its storage, transmission and display etc. As this multimedia data is mostly targeted to humans, multimedia researchers are working in field of incorporation of human’s perception, action related abilities. Detection of interesting content in images or videos based on human’s attention-based perspective is termed as Saliency. Various existing popular methods which have been used for saliency estimation were based on techniques like Difference of Gradients (DoG), K1 Divergence. These methods are time consuming and are applicable on selected parts of input only. This causes need to find a better approach which should be time-efficient and provides better results. In this paper Earth Mover’s Distance (EMD) based approach is adopted with bottom-up features-based saliency estimation for image and video data. Result shows that incorporation of EMD which is based on calculating histogram differences to find minimal cost incurred in transforming input data as close as output data, provides better results in terms of time consumption.

2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018

With the advancement of technology and easy accessibility of internet, an enormous amount of audi... more With the advancement of technology and easy accessibility of internet, an enormous amount of audio visual content is generated daily. This multimedia content takes a lot of space and time to be processed which decreases the performace of various video processing based applications like video searching, indexing, video recommendation and many more. The field of video summarization deals with the techniques for reducing the length of the video. Various state of the art techniques exists in this area and a lot of progress has been already done over the past years, but researchers are still working to generate more efficient and robust techniques, and to produce more accurate and sematically strong summarized videos The aim of this paper is to discuss about basic approaches for summarization, why it is so important in current scenario while keeping focus on the methods and recent approaches that have been introduced in last seven years in this area.

Advances in Communication, Cloud, and Big Data, 2018

The computer vision field deals with the problem of understanding the scene or features in images... more The computer vision field deals with the problem of understanding the scene or features in images of real world with the help of image processing and pattern recognition techniques. The main complication in this task is that the objects present in the images may have different appearances to the camera due to illumination effects, camera position, shadows, types of camera, etc. Nevertheless, with the advancement of technologies, today computer vision has provided reliable methods for various tasks like object classification, action recognition, autonomous driving, scene analysis, highlights extraction in videos and many more. But the problem of automatic qualifying is that how well people perform these actions has been largely unexplored. Human visual system and cognition can outperform the performance of computer vision algorithms. The objective of this paper is to highlight the state of the art of various psychological views of human visual perception in computer vision methods that have been found to operate well and that led up to the above-mentioned capabilities.

The digital cameras test scenes utilize a color channel cluster of mosaic example (e.g., the Baye... more The digital cameras test scenes utilize a color channel cluster of mosaic example (e.g., the Bayer example). The demosaicking of the color samples in [4] is basic to the picture essence. It displays another shading demosaicking procedure of ideal directional sifting of the greenred and greenblue contrast signals. Expecting it that the essential distinction signals (PDS) between the green and the red/blue channels are low pass, the missing green samples are robustly decided in both even and additionally vertical bearing by the direct least mean square-mistake estimation (LMMSE) procedure. These directional evaluations will be then ideally intertwined to further enhance the green gauges. In conclusion, guided by the demosaicked full-determination green channel, the other two shading channels are recreated from the LMMSE separated and intertwined PDS.

ion, Region level image abstraction, Color contrast estimation, Color distribution estimation, sp... more ion, Region level image abstraction, Color contrast estimation, Color distribution estimation, spatial saliency assignment and refinement, Center prior

Plants are the backbone of all life on Earth and an essential resource for human well-being. Plan... more Plants are the backbone of all life on Earth and an essential resource for human well-being. Plant recognition is very important in agriculture for the management of plant species whereas botanists can use this application for medicinal purposes. Leaf of different plants have different characteristics which can be used to classify them. This paper presents a simple and computationally efficient method for plant identification using digital image processing and machine vision technology. The proposed approach consists of three phases: pre-processing, feature extraction and classification. Preprocessing is the technique of enhancing data images prior to computational processing. The feature extraction phase derives features based on color and shape of the leaf image. These features are used as inputs to the classifier for efficient classification and the results were tested and compared using Artificial Neural Network (ANN) and Euclidean (KNN) classifier. The network was trained with ...

2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018

Now a days as the multimedia technologies being advances more video data is being produced and st... more Now a days as the multimedia technologies being advances more video data is being produced and stored daily which requires a lot of storage and complex video processing techniques. Video segmentation is a technique to extract useful segments from the video which can be used to develop various video processing based algorithms like video searching, video recommendation, video retrieval, surveillance etc. A lot of progress has been done in this area and researchers are still working due to the uncertain complexity of videos like motion of camera and object movement can impact the quality of video. Due to this evolving research area this paper discusses state of the art techniques for video segmentation. Then work done in past seven years which deals with various challenges in segmentation like motion blur, moving background, focusing, lighting has been analyzed. The paper is concluded with the future directions for the development of efficient algorithms for video segmentation.

Advances in Computer and Computational Sciences, 2017

Detection of objects for relocation in a video is a vital as well as initial step for many comput... more Detection of objects for relocation in a video is a vital as well as initial step for many computer vision-based applications like moving object extraction, video surveillance, pattern classification, etc. The traditional methods used for detection of foreground objects include background subtraction, optical flow and frame differencing techniques. These methods are found to be advantageous only if the extraction of the moving object is precise and clearly visible that it is, the object must be of good quality. This paper emphasizes on the detection as well as the enhancement of the foreground objects. The proposed method uses the amalgam of two traditional techniques background subtraction and motion vector-based optical flow method along with morphological operators to extricate the nonstationary objects from the videos followed by the enhancement of the extracted object to be of better quality in terms of visibility. The proposed algorithm is executed over the videos having frame dimension of 640 × 360 along with the frame rate of 30 frames/second using MATLAB R2013.

Neural Computing and Applications, 2021

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence, 2017

With the tremendous increase in video and image database there is a great need of automatic under... more With the tremendous increase in video and image database there is a great need of automatic understanding and examination of data by the intelligent systems as manually it is becoming out of reach. Narrowing it down to one specific domain, one of the most specific objects that can be traced in the images are people i.e. faces. Face detection is becoming a challenge by its increasing use in number of applications. It is the first step for face recognition, face analysis and detection of other features of face. In this paper, various face detection algorithms are discussed and analyzed like Viola-Jones, SMQT features & SNOW Classifier, Neural Network-Based Face Detection and Support Vector Machine-Based face detection. All these face detection methods are compared based on the precision and recall value calculated using a DetEval Software which deals with precised values of the bounding boxes around the faces to give accurate results.

2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT), 2018

Gesture Recognition has played a very significant role in the field of Human Computer Interaction... more Gesture Recognition has played a very significant role in the field of Human Computer Interaction (HCI). A vision-based hand gesture recognition approach can provide a significant solution to various machine vision-based applications by providing an easy interaction channel. For most of the automated machine control applications an efficient real time communication approach is required. In this paper a hand gesture-based approach is presented for providing a real time robotic control. The approach was tested on different gestures used to control the movements and the result shows that the proposed approach can be efficiently used in real time applications where immediate response of the system is more important.

Neural Computing and Applications, 2020

Brain computer interface (BCI) is the current trend in technology expansion as it provides an eas... more Brain computer interface (BCI) is the current trend in technology expansion as it provides an easy interface between human brain and machine. The demand for BCI based applications is growing tremendously and efforts are in progress to deploy BCI devices for real world applications. One of the widely known applications of BCI technology is rehabilitation in which BCI devices can provide various types of assistance to specially-abled persons. In this paper the effect of hand actions on objects is analyzed for motor related mental task. The proposed approach analysis electroencephalogram (EEG) based brain activity which was captured for images shown with different gripping actions on objects. The EEG recordings are first pre-processed, followed by extraction of epochs and frequency bands using discrete wavelet transform (DWT), afterwards feature extraction followed by training and classification steps are performed for classifying the grip action into congruent (correct) and incongruent (incorrect) grip categories. The proposed work makes use of average power and relative wavelet energy as discriminating features which are then fed to train an artificial neural network for automatically classifying the incoming EEG patterns into correct or incorrect object hand grips. The performance evaluation of proposed system is done on real EEG data set obtained from 14 subjects. Experimental results have shown an accuracy of 75%. Also, to evaluate the effectiveness of our work, a comparison of our work with other state of art works reported by different authors is presented at the end. The results show the effectiveness of proposed approach and suggest further that the system can be used for analyse and train subjects having motorrelated disabilities for perceiving correct or incorrect hand grips on objects.

CSI Transactions on ICT, 2016

Video summarization is very effective process in order to extract the essential and necessary inf... more Video summarization is very effective process in order to extract the essential and necessary information from huge videos and convert them into summarized videos. In this paper, we study and evaluate the comparative analysis of shot boundary detection algorithms of video summarization. The histogram based and edge based algorithms already exists are studied and compared with the new proposed improved histogram algorithm. The experimental evaluation validates the proposed approach returning most representative keyframes. The graphical representation of keyframes through above mentioned algorithms makes it clearer that new proposed algorithm delivers better and respectable results.

Advances in Intelligent Systems and Computing, 2016

The requirement of improved image processing methods to index increasing image database that resu... more The requirement of improved image processing methods to index increasing image database that results in an alarming need of content based image retrieval systems, which are search engines for images and also is an indexing technique for large collection of image databases. In this paper, an approach to improve the accuracy of content based image retrieval is proposed that uses the genetic algorithm, a novel and powerful global exploration approach. The classification techniques—Neural Network and Nearest Neighbor have been compared in the absence and presence of Genetic Algorithm. The computational results obtained shows the significant increase in the accuracy by incorporating genetic algorithm for both the classification techniques implemented.

One of the basic problems of user on manual wheelchair is overcoming architectural barriers (kerb... more One of the basic problems of user on manual wheelchair is overcoming architectural barriers (kerbs, stairs etc.) on its way. Even though many research studies have been reported in different fields to increase the independence of wheelchair users, the question of overcoming obstacles by a wheelchair always remains as topic of discussion for many researchers. In this paper, the author has proposed a manual stair climbing wheelchair concept which can overcome the architectural barriers to a considerable extent. Major part of the paper focuses on the proposed creative design concept and concludes by discussing upon the physical working model developed for the proposed design solution.

2014 IEEE International Conference on Computational Intelligence and Computing Research, 2014

In this particular paper has a purpose to explain a prominent This paper proposes an application ... more In this particular paper has a purpose to explain a prominent This paper proposes an application in which a gesture based interface is provided to enhance the physical world surrounds us with the digital world. The main purpose of this paper is to explain a prominent application using a microcontroller Atmega 328. This application put forward a new and exclusive technology to control BOT with the help of GUI in which the webcam acts as a digital eye which connects us with the information of digital world. Here, we used four colors i.e. red, green, yellow, blue which helps the webcam to recognize the gesture and performs different tasks or operations. The GUI helps to make the application much user-friendly, interactive and effective.

Advancements in Interdisciplinary Research

Proceedings of the Sixth International Conference on Computer and Communication Technology 2015

Nowadays, there are numerous, unstructured and voluminous videos which leads to high collection o... more Nowadays, there are numerous, unstructured and voluminous videos which leads to high collection of data on web. Searching and navigating through these videos for meaningful information is a time consuming task, whereas a good "summarized video" can provides a user determined information about particular video sequence in definite time limits. So, there is great need of extraction of semantic and useful information from videos for various multimedia applications. The video summarization is the novel and promising method of detecting relevant and informative data from videos and also aims to provide effective and efficient storage of relevant information. This technique of summarization leads to abstraction of most representative and relevant scenes from videos and concatenates to display as one successive and uninterrupted video and thus has been powered up the rapidly progressing research domain. In this paper, all latest and enhanced approaches of video shot detection have been discussed and summarized.

Interdisciplinary Innovations and Developments towards Smart and Sustainable Industries

He has 18 years of teaching and research experience. Dr. Kumar has published more than 100 resear... more He has 18 years of teaching and research experience. Dr. Kumar has published more than 100 research articles in journals and conferences of repute; and supervised 5 Ph.D. and approximately 50 M.Tech. Theses. His current research interests include the

U.Porto Journal of Engineering

In recent times, the computer vision community has seen remarkable growth in the field of scene u... more In recent times, the computer vision community has seen remarkable growth in the field of scene understanding. With such a wide prevalence of images, the importance of this field is growing rapidly along with the technologies involved in it. Semantic Segmentation is an important step in scene understanding which requires the assignment of each pixel in an image to a pre-defined class and achieving 100% accuracy is a challenging task, thereby making it an active research topic among researchers. In this paper, an extensive study and review of the existing Deep Learning (DL) based techniques used for Semantic Segmentation is carried out along with a summary of the datasets and evaluation metrics used for it. The study involved the meticulous selection of relevant research papers in the field of interest by search based on several defined keywords. The study begins with a general and broader focus on Semantic Segmentation as a problem and further narrows its focus on existing Deep Lear...

2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)

The advancement of multimedia technology has increased the problem of its storage, transmission a... more The advancement of multimedia technology has increased the problem of its storage, transmission and display etc. As this multimedia data is mostly targeted to humans, multimedia researchers are working in field of incorporation of human’s perception, action related abilities. Detection of interesting content in images or videos based on human’s attention-based perspective is termed as Saliency. Various existing popular methods which have been used for saliency estimation were based on techniques like Difference of Gradients (DoG), K1 Divergence. These methods are time consuming and are applicable on selected parts of input only. This causes need to find a better approach which should be time-efficient and provides better results. In this paper Earth Mover’s Distance (EMD) based approach is adopted with bottom-up features-based saliency estimation for image and video data. Result shows that incorporation of EMD which is based on calculating histogram differences to find minimal cost incurred in transforming input data as close as output data, provides better results in terms of time consumption.

2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018

With the advancement of technology and easy accessibility of internet, an enormous amount of audi... more With the advancement of technology and easy accessibility of internet, an enormous amount of audio visual content is generated daily. This multimedia content takes a lot of space and time to be processed which decreases the performace of various video processing based applications like video searching, indexing, video recommendation and many more. The field of video summarization deals with the techniques for reducing the length of the video. Various state of the art techniques exists in this area and a lot of progress has been already done over the past years, but researchers are still working to generate more efficient and robust techniques, and to produce more accurate and sematically strong summarized videos The aim of this paper is to discuss about basic approaches for summarization, why it is so important in current scenario while keeping focus on the methods and recent approaches that have been introduced in last seven years in this area.

Advances in Communication, Cloud, and Big Data, 2018

The computer vision field deals with the problem of understanding the scene or features in images... more The computer vision field deals with the problem of understanding the scene or features in images of real world with the help of image processing and pattern recognition techniques. The main complication in this task is that the objects present in the images may have different appearances to the camera due to illumination effects, camera position, shadows, types of camera, etc. Nevertheless, with the advancement of technologies, today computer vision has provided reliable methods for various tasks like object classification, action recognition, autonomous driving, scene analysis, highlights extraction in videos and many more. But the problem of automatic qualifying is that how well people perform these actions has been largely unexplored. Human visual system and cognition can outperform the performance of computer vision algorithms. The objective of this paper is to highlight the state of the art of various psychological views of human visual perception in computer vision methods that have been found to operate well and that led up to the above-mentioned capabilities.

The digital cameras test scenes utilize a color channel cluster of mosaic example (e.g., the Baye... more The digital cameras test scenes utilize a color channel cluster of mosaic example (e.g., the Bayer example). The demosaicking of the color samples in [4] is basic to the picture essence. It displays another shading demosaicking procedure of ideal directional sifting of the greenred and greenblue contrast signals. Expecting it that the essential distinction signals (PDS) between the green and the red/blue channels are low pass, the missing green samples are robustly decided in both even and additionally vertical bearing by the direct least mean square-mistake estimation (LMMSE) procedure. These directional evaluations will be then ideally intertwined to further enhance the green gauges. In conclusion, guided by the demosaicked full-determination green channel, the other two shading channels are recreated from the LMMSE separated and intertwined PDS.

ion, Region level image abstraction, Color contrast estimation, Color distribution estimation, sp... more ion, Region level image abstraction, Color contrast estimation, Color distribution estimation, spatial saliency assignment and refinement, Center prior

Plants are the backbone of all life on Earth and an essential resource for human well-being. Plan... more Plants are the backbone of all life on Earth and an essential resource for human well-being. Plant recognition is very important in agriculture for the management of plant species whereas botanists can use this application for medicinal purposes. Leaf of different plants have different characteristics which can be used to classify them. This paper presents a simple and computationally efficient method for plant identification using digital image processing and machine vision technology. The proposed approach consists of three phases: pre-processing, feature extraction and classification. Preprocessing is the technique of enhancing data images prior to computational processing. The feature extraction phase derives features based on color and shape of the leaf image. These features are used as inputs to the classifier for efficient classification and the results were tested and compared using Artificial Neural Network (ANN) and Euclidean (KNN) classifier. The network was trained with ...

2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2018

Now a days as the multimedia technologies being advances more video data is being produced and st... more Now a days as the multimedia technologies being advances more video data is being produced and stored daily which requires a lot of storage and complex video processing techniques. Video segmentation is a technique to extract useful segments from the video which can be used to develop various video processing based algorithms like video searching, video recommendation, video retrieval, surveillance etc. A lot of progress has been done in this area and researchers are still working due to the uncertain complexity of videos like motion of camera and object movement can impact the quality of video. Due to this evolving research area this paper discusses state of the art techniques for video segmentation. Then work done in past seven years which deals with various challenges in segmentation like motion blur, moving background, focusing, lighting has been analyzed. The paper is concluded with the future directions for the development of efficient algorithms for video segmentation.

Advances in Computer and Computational Sciences, 2017

Detection of objects for relocation in a video is a vital as well as initial step for many comput... more Detection of objects for relocation in a video is a vital as well as initial step for many computer vision-based applications like moving object extraction, video surveillance, pattern classification, etc. The traditional methods used for detection of foreground objects include background subtraction, optical flow and frame differencing techniques. These methods are found to be advantageous only if the extraction of the moving object is precise and clearly visible that it is, the object must be of good quality. This paper emphasizes on the detection as well as the enhancement of the foreground objects. The proposed method uses the amalgam of two traditional techniques background subtraction and motion vector-based optical flow method along with morphological operators to extricate the nonstationary objects from the videos followed by the enhancement of the extracted object to be of better quality in terms of visibility. The proposed algorithm is executed over the videos having frame dimension of 640 × 360 along with the frame rate of 30 frames/second using MATLAB R2013.

Neural Computing and Applications, 2021

2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence, 2017

With the tremendous increase in video and image database there is a great need of automatic under... more With the tremendous increase in video and image database there is a great need of automatic understanding and examination of data by the intelligent systems as manually it is becoming out of reach. Narrowing it down to one specific domain, one of the most specific objects that can be traced in the images are people i.e. faces. Face detection is becoming a challenge by its increasing use in number of applications. It is the first step for face recognition, face analysis and detection of other features of face. In this paper, various face detection algorithms are discussed and analyzed like Viola-Jones, SMQT features & SNOW Classifier, Neural Network-Based Face Detection and Support Vector Machine-Based face detection. All these face detection methods are compared based on the precision and recall value calculated using a DetEval Software which deals with precised values of the bounding boxes around the faces to give accurate results.

2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT), 2018

Gesture Recognition has played a very significant role in the field of Human Computer Interaction... more Gesture Recognition has played a very significant role in the field of Human Computer Interaction (HCI). A vision-based hand gesture recognition approach can provide a significant solution to various machine vision-based applications by providing an easy interaction channel. For most of the automated machine control applications an efficient real time communication approach is required. In this paper a hand gesture-based approach is presented for providing a real time robotic control. The approach was tested on different gestures used to control the movements and the result shows that the proposed approach can be efficiently used in real time applications where immediate response of the system is more important.

Neural Computing and Applications, 2020

Brain computer interface (BCI) is the current trend in technology expansion as it provides an eas... more Brain computer interface (BCI) is the current trend in technology expansion as it provides an easy interface between human brain and machine. The demand for BCI based applications is growing tremendously and efforts are in progress to deploy BCI devices for real world applications. One of the widely known applications of BCI technology is rehabilitation in which BCI devices can provide various types of assistance to specially-abled persons. In this paper the effect of hand actions on objects is analyzed for motor related mental task. The proposed approach analysis electroencephalogram (EEG) based brain activity which was captured for images shown with different gripping actions on objects. The EEG recordings are first pre-processed, followed by extraction of epochs and frequency bands using discrete wavelet transform (DWT), afterwards feature extraction followed by training and classification steps are performed for classifying the grip action into congruent (correct) and incongruent (incorrect) grip categories. The proposed work makes use of average power and relative wavelet energy as discriminating features which are then fed to train an artificial neural network for automatically classifying the incoming EEG patterns into correct or incorrect object hand grips. The performance evaluation of proposed system is done on real EEG data set obtained from 14 subjects. Experimental results have shown an accuracy of 75%. Also, to evaluate the effectiveness of our work, a comparison of our work with other state of art works reported by different authors is presented at the end. The results show the effectiveness of proposed approach and suggest further that the system can be used for analyse and train subjects having motorrelated disabilities for perceiving correct or incorrect hand grips on objects.

CSI Transactions on ICT, 2016

Video summarization is very effective process in order to extract the essential and necessary inf... more Video summarization is very effective process in order to extract the essential and necessary information from huge videos and convert them into summarized videos. In this paper, we study and evaluate the comparative analysis of shot boundary detection algorithms of video summarization. The histogram based and edge based algorithms already exists are studied and compared with the new proposed improved histogram algorithm. The experimental evaluation validates the proposed approach returning most representative keyframes. The graphical representation of keyframes through above mentioned algorithms makes it clearer that new proposed algorithm delivers better and respectable results.

Advances in Intelligent Systems and Computing, 2016

The requirement of improved image processing methods to index increasing image database that resu... more The requirement of improved image processing methods to index increasing image database that results in an alarming need of content based image retrieval systems, which are search engines for images and also is an indexing technique for large collection of image databases. In this paper, an approach to improve the accuracy of content based image retrieval is proposed that uses the genetic algorithm, a novel and powerful global exploration approach. The classification techniques—Neural Network and Nearest Neighbor have been compared in the absence and presence of Genetic Algorithm. The computational results obtained shows the significant increase in the accuracy by incorporating genetic algorithm for both the classification techniques implemented.

One of the basic problems of user on manual wheelchair is overcoming architectural barriers (kerb... more One of the basic problems of user on manual wheelchair is overcoming architectural barriers (kerbs, stairs etc.) on its way. Even though many research studies have been reported in different fields to increase the independence of wheelchair users, the question of overcoming obstacles by a wheelchair always remains as topic of discussion for many researchers. In this paper, the author has proposed a manual stair climbing wheelchair concept which can overcome the architectural barriers to a considerable extent. Major part of the paper focuses on the proposed creative design concept and concludes by discussing upon the physical working model developed for the proposed design solution.

2014 IEEE International Conference on Computational Intelligence and Computing Research, 2014

In this particular paper has a purpose to explain a prominent This paper proposes an application ... more In this particular paper has a purpose to explain a prominent This paper proposes an application in which a gesture based interface is provided to enhance the physical world surrounds us with the digital world. The main purpose of this paper is to explain a prominent application using a microcontroller Atmega 328. This application put forward a new and exclusive technology to control BOT with the help of GUI in which the webcam acts as a digital eye which connects us with the information of digital world. Here, we used four colors i.e. red, green, yellow, blue which helps the webcam to recognize the gesture and performs different tasks or operations. The GUI helps to make the application much user-friendly, interactive and effective.