MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

School of Electronics & Communication Engineering

World University root node

Engineering and Technology

Performance Comparisons of Gradual Transition Detection Methods

Wireless Transmission of Stereo Images and its Disparity Levels

International Journal of Graphics &amp; Image Processing

Computer Vision Application For Automatic Human Behaviour Recognition

Radiologist analyzes thousands of mammograms daily and this causes fatigue and eye strain. Out of thousands of cases, not more than 10 have breast cancer tissues and thus an abnormality might not be detected. To assist radiologists in order to detect mammographic abnormalities, computer-aided detection (CAD) algorithms are developed. This work proposes a CAD system which makes use of principal and independent component analysis (PCA and ICA). Classifiers used in this work are support vector machines (SVMs), classifier and artificial neural network (ANN) classifier. SVM or ANN identifies the suspicious regions and classifies them into the labels assigned. PCA which is a necessary pre-processing step for ICA reduces the dimensionality of the input images. ICA extracts the maximum independent features from the reduced data set and then SVM or ANN classifies the test image into normal or malignant. A comparative analysis of the classification accuracy by using ANN and SVM as classifier is done. For both these classifiers, different numbers of principal components are experimented. © 2014 WIT Press.

WIT Transactions on Information and Communication Technologies

Comparison of SVM and ANN classifier for mammogram classification using ICA features

The detection of moving object is fundamental to automated video surveillance, object analysis and recognition. It involves the trajectory of an object over time by locating its position in every frame of the video. In this paper we implement a moving object detection method on FPGA. Detection of moving object is a challenging task. In our implementation of the design we used the background subtraction based method. Background subtraction is a method which detects moving objects from reference background image. Experiment is carried out in MATLAB and on FPGA board. © 2014 IEEE.

2014 International Conference on Computer Communication and Informatics: Ushering in Technologies of Tomorrow, Today, ICCCI 2014

FPGA based moving object detection

Digital video sequences in uncompressed form require huge storage and high transmission bandwidth for multimedia communication. The increasing number of Video over Wireless (VoW) services is creating greater thrust for higher coding efficiency for digital video signals. Efficient coding and transmission control techniques are required to meet the needs of Quality of Service (QoS). H.264/MPEG4-advanced video coding (AVC) video enCOder/DECoder (CODEC) is the latest coding and compression standard from the International Telecommunications Union-Telecommunication (ITU-T). This standard is currently dominating the field by offering a flexible architecture and compression gain for video coding. Due to its high compression efficiency with low compression delay, it is used in many real time VoW transmission applications. Modern wireless networks provide many different means to adapt QoS like low end-to-end delay, efficient bandwidth-utilization and lower bit-rate. This paper presents a design of integrated CODEC scheme with relatively lower bit-rate and improved edge peak signal-to-noise ratio (EPSNR). Several important factors of video sequence are analyzed for achieving lower bit-rate. A new scheme is proposed at Application (APP) layer for video compression, called as Enhanced Intra Prediction (EnIP). This algorithm uses picture structure without B-pictures for real time VoW application. The proposed algorithm is implemented on TMS320DM6437; a multimedia processor, using Digital Video Development Platform (DVDP). The superior performance of the proposed EnIP algorithm is validated by experimental results. It shows that the implementation of EnIP using digital multimedia processor lowers the bit-rate and improves EPSNR significantly. © 2014 Springer Science+Business Media New York.

Wireless personal communications

Improved Compression Performance of H. 264/MPEG4-AVC for Digital Video Using DVDP

International Journal of Computer Architecture and Mobility (ISSN 2319-9229) Volume

Optimal side lobe reduction of linear non-uniform array using genetic algorithm

International Journal of Engineering Research and Technology

Smart Antenna Optimization Algorithms

The purpose of this study was to develop a methodology for assessing fruit quality objectively using texture analysis based on Curvelet Transform. Being a multiresolution approach, curvelets have the capability to examine fruit surface at low and high resolution to extract both global and local details about fruit surface. The fruit images were acquired using a CCD color camera and guava and lemon were analyzed by experimentation. Textural measures based on curvelet transform such as energy, entropy, mean and standard deviation were used to characterize fruits'surface texture. The discriminating powers of these features for fruit quality grading is investigated. The acquired features were subjected to classifiers such as Support Vector Machines (SVM) and Probabilistic Neural Networks (PNN) and the performance of classifiers was tested for the two category grading of fruits namely healthy and defected. The results showed that best SVM classification was obtained with an accuracy of 96%. The study concludes that curvelet based textural features gives promising insights to estimate fruit's skin damages.

International Journal of Engineering and Technology

Automated skin defect identification system for fruit grading based on discrete curvelet transform

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International Journal of Advanced Computer Science and Applications

Performance of Turbo Product Code in Wimax