Anita Thengade - Academia.edu (original) (raw)
Papers by Anita Thengade
International journal of engineering trends and technology, Feb 3, 2024
International journal of engineering research and technology, Feb 28, 2013
Advances in intelligent systems and computing, 2020
Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthr... more Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthritis (KOA) progression. In general, it is a primary concern to segment, detect and extract the defects from knee magnetic resonance images (MRI). Conventionally, this process is carried out manually in clinical practice but it is time consuming and observer dependent. It is a big challenge to segment cartilage manually from MRI, as cartilage structure has inadequate image contrast and complex tissue structure. Currently, semiautomatic and automatic methods are used to overcome this limitation. In the proposed method, we present a segmentation approach for the extraction of bone and cartilage from MRI. Here, in this paper we perform preprocessing for image enhancement and noise removal of knee MR image using Gaussian blur and block matching 3D method. Larger bones in the knee joint are segmented first to perform reliable cartilage segmentation. Hence distance regularization level set evolution (DRLSE) is used for bone extraction successively followed by cartilage segmentation. Further, the performance of the proposed method is analyzed on a variety of knee MR images and experimental results demonstrated the improvement in accuracy compared to existing approaches. In conclusion, it is observed that the proposed technique improves significant performance with consistency and robustness during the segmentation process.
Use of computer science in the field of medical gives the major importance to the world. Hence in... more Use of computer science in the field of medical gives the major importance to the world. Hence in the medical field we use the technology in order to help the doctor to diagnose the disease. In this paper we make use of the segmentation technique on the MRI (Magnetic Resonance Images) data to diagnose the osteoarthritis. Osteoarthritis is a knee joint disease and in this paper we are mainly focused on the cartilage degradation i.e., degrading the femur and tibia cartilage. Image Segmentation provides the analysis of the image and extracts the data in order to perform the operation on it. This paper lists out various image segmentation techniques, to perform the segmentation of the knee cartilage from magnetic resonance images (MRI). The segmentation technique by the rough fuzzy c means classifier which provides the degrade in cartilage region and the SVM (support vector Machine) technique is used to classify the degradation cartilage.
Social Science Research Network, 2021
2022 Second International Conference on Next Generation Intelligent Systems (ICNGIS), Jul 29, 2022
Graduate Research in Engineering and Technology
Literate population is an important asset for any nation & plays a crucial role while representin... more Literate population is an important asset for any nation & plays a crucial role while representing the country at internationals. Education makes the backbone of the society, which reveals the skills, knowledge and behaviour transferred from one generation to the next generation. During COVID 19 pandemic, major changes can be seen in the education system. Class room teaching is replaced by an online teaching model to facilitate the students to continue their education. Online teaching methods were adopted by the teachers to maintain the students' learning at all levels. The pandemic has resulted in a change of teaching patterns from traditional classrooms to digital pedagogies. The teaching has become more student oriented rather than on-way teaching methods. These new innovative and active learning practices for teaching pedagogy have enabled the smart teachings for the Education era. The main actor for the Project-based learning is a student, where he/she explores the real-wor...
2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), 2018
Use of computer science in the field of medical gives the major importance to the world. Hence in... more Use of computer science in the field of medical gives the major importance to the world. Hence in the medical field we use the technology in order to help the doctor to diagnose the disease. In this paper we make use of the segmentation technique on the MRI (Magnetic Resonance Images) data to diagnose the osteoarthritis. Osteoarthritis is a knee joint disease and in this paper we are mainly focused on the cartilage degradation i.e., degrading the femur and tibia cartilage. Image Segmentation provides the analysis of the image and extracts the data in order to perform the operation on it. This paper lists out various image segmentation techniques, to perform the segmentation of the knee cartilage from magnetic resonance images (MRI). The segmentation technique by the rough fuzzy c means classifier which provides the degrade in cartilage region and the SVM (support vector Machine) technique is used to classify the degradation cartilage.
Applied Computer Vision and Image Processing, 2020
Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthr... more Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthritis (KOA) progression. In general, it is a primary concern to segment, detect and extract the defects from knee magnetic resonance images (MRI). Conventionally, this process is carried out manually in clinical practice but it is time consuming and observer dependent. It is a big challenge to segment cartilage manually from MRI, as cartilage structure has inadequate image contrast and complex tissue structure. Currently, semiautomatic and automatic methods are used to overcome this limitation. In the proposed method, we present a segmentation approach for the extraction of bone and cartilage from MRI. Here, in this paper we perform preprocessing for image enhancement and noise removal of knee MR image using Gaussian blur and block matching 3D method. Larger bones in the knee joint are segmented first to perform reliable cartilage segmentation. Hence distance regularization level set evolution (DRLSE) is used for bone extraction successively followed by cartilage segmentation. Further, the performance of the proposed method is analyzed on a variety of knee MR images and experimental results demonstrated the improvement in accuracy compared to existing approaches. In conclusion, it is observed that the proposed technique improves significant performance with consistency and robustness during the segmentation process.
Computational Vision and Bio-Inspired Computing, 2020
Biometrics is a dynamic industry resulting in sustained evolution of numerous new technologies. T... more Biometrics is a dynamic industry resulting in sustained evolution of numerous new technologies. The biometric system is needed in many key areas such as banking, airport, criminal cases, security purpose etc. Gait is an important biometric technology to recognize a human by the manner, they walk. Biometric identification based on body movements as gait recognition has gained new motivation over the past few years due to the launch of low cost depth cameras. Here, we propose a model to identify the human without coordination using gait images. In this paper we propose the biometric system to distinguish human from others through gait images based on principal component analysis algorithm and K nearest neighbor classifier. Principal component analysis is used to extract gait features. K nearest neighbor classifier is used to compute human id. Experimental analyses on CASIA A dataset show a significant performance gain in terms of accuracy. We create our own dataset for experiment usin...
Deep learning of a person’s signature can reveal his personality profile like fear, honesty, emot... more Deep learning of a person’s signature can reveal his personality profile like fear, honesty, emotional state, thinking style and much more. Analyzing signature can help in predicting social skills, thinking style, work habits, achievements, etc. of the writer. Type and style of signature can be judged by graphologist based on curved start, single line, dot on letter, etc. Similarly pattern recognition and image processing are used to analyze signature and handwriting in our system. Here the signature is considered as image and then prediction is performed through different stages such as gray level conversion, calculating threshold value, binary conversion etc. The most preferred technique by researchers for personality prediction is 'Artificial Neural Network'. Keywords— Signature Analysis, Personality Prediction, Graphology, Artificial Neural Network, Human Personality, Personality, Signature.
The fire can be recognised effectively through video image processing. Traditional fire recogniti... more The fire can be recognised effectively through video image processing. Traditional fire recognition system based on video image analysis do not analyze the color,texture and low level visual feature information of specific fire image.The validation performance is not good,the fire image scene recognition method is proposed on image processing .A contour is a curve joining all the continuous points along the boundary with the same color value. The detecting of contours in an image is very useful if you want to detect the boundaries in images.Gray processing and binaryzation process are taken into consideration for fire image.The normalization process is taken for filtering background interface.The refined video digital image is analyzed . Fire Sensor is used to collect the visual feature of fire video monitoring images.Simulation shows algorithm has good efficiency it can recognize campus fire accurately and gives real time alarming.
There are a variety of viruses out there infecting computers in newer ways that are difficult to ... more There are a variety of viruses out there infecting computers in newer ways that are difficult to trace. The most common way of detecting a virus is waiting for the virus to spread its reach on many computers, recognizing its mechanism and then designing a method to fight against that specific virus. However, this means that we can only devise a solution after a number of computers have been infected. Moreover, the metamorphic viruses are designed such that they are capable of changing their structure after every attack. Static signature detection can do little against viruses of these types. In this paper, we explore the different types of viruses so as to better equip ourselves to determine methods to detect them. We then study various virus detection techniques and shed light on the limitations of these techniques.
Applied Computer Vision and Image Processing, 2020
Human Gait refers to motion accomplished through the movement of hand limbs. Gait analysis is a p... more Human Gait refers to motion accomplished through the movement of hand limbs. Gait analysis is a precise investigation of the human walking pattern using sensors attached to the body for recording body movements during activities like walking on a flat surface, treadmill and running. This paper addresses the analysis of human gait based on performance using various classification techniques involving Decision Tree, Random Forest and KNN algorithms. The paper highlights the comparison of these classification models based on various parameters using the RapidMiner Studio tool. The comparison is based on performance metrics and Receiver Operating Characteristic (ROC). The results show that the Random Forest algorithm performs better in classifying normal and abnormal gait.
Technology and Tools in Engineering Education, 2021
Today, with the new advances in technology, there is a need to have innovative and active learnin... more Today, with the new advances in technology, there is a need to have innovative and active learning practices for Teaching. Now, it’s the student-centric Education era. As quoted by John Holt, “ Learning is not the product of teaching but Learning is the product of the activity of Learners ”. The proper learning at proper life span of a student plays a vital role in the mental as well as physical growth of that student. There are various types of learnings known as teaching pedagogies to have the two way interactive sessions. The student’s suggestions should be honored by giving them chance to express themselves and thus increasing the teaching–learning interactions. The teaching–learning sessions needs to be “Learner-centered” rather than “Teacher-centered” in classroom. Thus, it’s the modern pedagogy that has learner diversity, where the Teacher has to cater to the diversity of learning styles and acts more like a Facilitator. The active learning pedagogies will definitely motivate and increase the active participation of the students in classroom.
Ijca Proceedings on National Conference on Recent Trends in Computing, May 12, 2012
Research Advances in the Integration of Big Data and Smart Computing
International journal of engineering trends and technology, Feb 3, 2024
International journal of engineering research and technology, Feb 28, 2013
Advances in intelligent systems and computing, 2020
Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthr... more Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthritis (KOA) progression. In general, it is a primary concern to segment, detect and extract the defects from knee magnetic resonance images (MRI). Conventionally, this process is carried out manually in clinical practice but it is time consuming and observer dependent. It is a big challenge to segment cartilage manually from MRI, as cartilage structure has inadequate image contrast and complex tissue structure. Currently, semiautomatic and automatic methods are used to overcome this limitation. In the proposed method, we present a segmentation approach for the extraction of bone and cartilage from MRI. Here, in this paper we perform preprocessing for image enhancement and noise removal of knee MR image using Gaussian blur and block matching 3D method. Larger bones in the knee joint are segmented first to perform reliable cartilage segmentation. Hence distance regularization level set evolution (DRLSE) is used for bone extraction successively followed by cartilage segmentation. Further, the performance of the proposed method is analyzed on a variety of knee MR images and experimental results demonstrated the improvement in accuracy compared to existing approaches. In conclusion, it is observed that the proposed technique improves significant performance with consistency and robustness during the segmentation process.
Use of computer science in the field of medical gives the major importance to the world. Hence in... more Use of computer science in the field of medical gives the major importance to the world. Hence in the medical field we use the technology in order to help the doctor to diagnose the disease. In this paper we make use of the segmentation technique on the MRI (Magnetic Resonance Images) data to diagnose the osteoarthritis. Osteoarthritis is a knee joint disease and in this paper we are mainly focused on the cartilage degradation i.e., degrading the femur and tibia cartilage. Image Segmentation provides the analysis of the image and extracts the data in order to perform the operation on it. This paper lists out various image segmentation techniques, to perform the segmentation of the knee cartilage from magnetic resonance images (MRI). The segmentation technique by the rough fuzzy c means classifier which provides the degrade in cartilage region and the SVM (support vector Machine) technique is used to classify the degradation cartilage.
Social Science Research Network, 2021
2022 Second International Conference on Next Generation Intelligent Systems (ICNGIS), Jul 29, 2022
Graduate Research in Engineering and Technology
Literate population is an important asset for any nation & plays a crucial role while representin... more Literate population is an important asset for any nation & plays a crucial role while representing the country at internationals. Education makes the backbone of the society, which reveals the skills, knowledge and behaviour transferred from one generation to the next generation. During COVID 19 pandemic, major changes can be seen in the education system. Class room teaching is replaced by an online teaching model to facilitate the students to continue their education. Online teaching methods were adopted by the teachers to maintain the students' learning at all levels. The pandemic has resulted in a change of teaching patterns from traditional classrooms to digital pedagogies. The teaching has become more student oriented rather than on-way teaching methods. These new innovative and active learning practices for teaching pedagogy have enabled the smart teachings for the Education era. The main actor for the Project-based learning is a student, where he/she explores the real-wor...
2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA), 2018
Use of computer science in the field of medical gives the major importance to the world. Hence in... more Use of computer science in the field of medical gives the major importance to the world. Hence in the medical field we use the technology in order to help the doctor to diagnose the disease. In this paper we make use of the segmentation technique on the MRI (Magnetic Resonance Images) data to diagnose the osteoarthritis. Osteoarthritis is a knee joint disease and in this paper we are mainly focused on the cartilage degradation i.e., degrading the femur and tibia cartilage. Image Segmentation provides the analysis of the image and extracts the data in order to perform the operation on it. This paper lists out various image segmentation techniques, to perform the segmentation of the knee cartilage from magnetic resonance images (MRI). The segmentation technique by the rough fuzzy c means classifier which provides the degrade in cartilage region and the SVM (support vector Machine) technique is used to classify the degradation cartilage.
Applied Computer Vision and Image Processing, 2020
Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthr... more Segmentation of knee joint is an instrumental task in a medical fraternity during knee osteoarthritis (KOA) progression. In general, it is a primary concern to segment, detect and extract the defects from knee magnetic resonance images (MRI). Conventionally, this process is carried out manually in clinical practice but it is time consuming and observer dependent. It is a big challenge to segment cartilage manually from MRI, as cartilage structure has inadequate image contrast and complex tissue structure. Currently, semiautomatic and automatic methods are used to overcome this limitation. In the proposed method, we present a segmentation approach for the extraction of bone and cartilage from MRI. Here, in this paper we perform preprocessing for image enhancement and noise removal of knee MR image using Gaussian blur and block matching 3D method. Larger bones in the knee joint are segmented first to perform reliable cartilage segmentation. Hence distance regularization level set evolution (DRLSE) is used for bone extraction successively followed by cartilage segmentation. Further, the performance of the proposed method is analyzed on a variety of knee MR images and experimental results demonstrated the improvement in accuracy compared to existing approaches. In conclusion, it is observed that the proposed technique improves significant performance with consistency and robustness during the segmentation process.
Computational Vision and Bio-Inspired Computing, 2020
Biometrics is a dynamic industry resulting in sustained evolution of numerous new technologies. T... more Biometrics is a dynamic industry resulting in sustained evolution of numerous new technologies. The biometric system is needed in many key areas such as banking, airport, criminal cases, security purpose etc. Gait is an important biometric technology to recognize a human by the manner, they walk. Biometric identification based on body movements as gait recognition has gained new motivation over the past few years due to the launch of low cost depth cameras. Here, we propose a model to identify the human without coordination using gait images. In this paper we propose the biometric system to distinguish human from others through gait images based on principal component analysis algorithm and K nearest neighbor classifier. Principal component analysis is used to extract gait features. K nearest neighbor classifier is used to compute human id. Experimental analyses on CASIA A dataset show a significant performance gain in terms of accuracy. We create our own dataset for experiment usin...
Deep learning of a person’s signature can reveal his personality profile like fear, honesty, emot... more Deep learning of a person’s signature can reveal his personality profile like fear, honesty, emotional state, thinking style and much more. Analyzing signature can help in predicting social skills, thinking style, work habits, achievements, etc. of the writer. Type and style of signature can be judged by graphologist based on curved start, single line, dot on letter, etc. Similarly pattern recognition and image processing are used to analyze signature and handwriting in our system. Here the signature is considered as image and then prediction is performed through different stages such as gray level conversion, calculating threshold value, binary conversion etc. The most preferred technique by researchers for personality prediction is 'Artificial Neural Network'. Keywords— Signature Analysis, Personality Prediction, Graphology, Artificial Neural Network, Human Personality, Personality, Signature.
The fire can be recognised effectively through video image processing. Traditional fire recogniti... more The fire can be recognised effectively through video image processing. Traditional fire recognition system based on video image analysis do not analyze the color,texture and low level visual feature information of specific fire image.The validation performance is not good,the fire image scene recognition method is proposed on image processing .A contour is a curve joining all the continuous points along the boundary with the same color value. The detecting of contours in an image is very useful if you want to detect the boundaries in images.Gray processing and binaryzation process are taken into consideration for fire image.The normalization process is taken for filtering background interface.The refined video digital image is analyzed . Fire Sensor is used to collect the visual feature of fire video monitoring images.Simulation shows algorithm has good efficiency it can recognize campus fire accurately and gives real time alarming.
There are a variety of viruses out there infecting computers in newer ways that are difficult to ... more There are a variety of viruses out there infecting computers in newer ways that are difficult to trace. The most common way of detecting a virus is waiting for the virus to spread its reach on many computers, recognizing its mechanism and then designing a method to fight against that specific virus. However, this means that we can only devise a solution after a number of computers have been infected. Moreover, the metamorphic viruses are designed such that they are capable of changing their structure after every attack. Static signature detection can do little against viruses of these types. In this paper, we explore the different types of viruses so as to better equip ourselves to determine methods to detect them. We then study various virus detection techniques and shed light on the limitations of these techniques.
Applied Computer Vision and Image Processing, 2020
Human Gait refers to motion accomplished through the movement of hand limbs. Gait analysis is a p... more Human Gait refers to motion accomplished through the movement of hand limbs. Gait analysis is a precise investigation of the human walking pattern using sensors attached to the body for recording body movements during activities like walking on a flat surface, treadmill and running. This paper addresses the analysis of human gait based on performance using various classification techniques involving Decision Tree, Random Forest and KNN algorithms. The paper highlights the comparison of these classification models based on various parameters using the RapidMiner Studio tool. The comparison is based on performance metrics and Receiver Operating Characteristic (ROC). The results show that the Random Forest algorithm performs better in classifying normal and abnormal gait.
Technology and Tools in Engineering Education, 2021
Today, with the new advances in technology, there is a need to have innovative and active learnin... more Today, with the new advances in technology, there is a need to have innovative and active learning practices for Teaching. Now, it’s the student-centric Education era. As quoted by John Holt, “ Learning is not the product of teaching but Learning is the product of the activity of Learners ”. The proper learning at proper life span of a student plays a vital role in the mental as well as physical growth of that student. There are various types of learnings known as teaching pedagogies to have the two way interactive sessions. The student’s suggestions should be honored by giving them chance to express themselves and thus increasing the teaching–learning interactions. The teaching–learning sessions needs to be “Learner-centered” rather than “Teacher-centered” in classroom. Thus, it’s the modern pedagogy that has learner diversity, where the Teacher has to cater to the diversity of learning styles and acts more like a Facilitator. The active learning pedagogies will definitely motivate and increase the active participation of the students in classroom.
Ijca Proceedings on National Conference on Recent Trends in Computing, May 12, 2012
Research Advances in the Integration of Big Data and Smart Computing