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 Computer Engineering & Technology

World University root node

Engineering and Technology

International Journal of Distributed and Parallel Systems

Analysis and comparison of distance vector, DSDV and AODV protocol of MANET

Printed character recognition is important in the context of document image analysis. Document image analysis analyzes the document images to extract the text and graphics information from image. Text extraction is followed by the character recognition .This paper reviews various phases of machine printed character recognition in document image. © 2012 Published by Elsevier Ltd.

Fulltext

Procedia Engineering

Computer assisted printed character recognition in document based images

In this paper we propose a novel face detection approach. In general, lighting in images can have negative impact on the performance of face detection systems. Many current face detection systems are only reliable under controlled condition such as indoors under stable lighting conditions. So there is need to devise a solution to overcome illumination problems faced by face detection system. As one of the solution proposed approach firstly adopts a 'reference white' to realize light compensation; Then it realizes the detection of candidate face region using Ycbcr skin color model. The third, paper uses well known opening and closing morphological operations to exclude the impact of noise on color segmentation. Last Adaboost algorithm is improved and used to accurate face detection. The system uses java to achieve and is verified in self designed photo library, and is particularly suitable for illumination variations and complex background. © 2012 IEEE.

Proceedings - 2012 International Conference on Communication, Information and Computing Technology, ICCICT 2012

Reliable face detection in varying illumination and complex background

This paper presents a technique based on statistical and neural feature extractor, classifier and retrieval for real world texture images. The paper is presented into two stages, texture image pre-processing includes downloading images, normalizing into specific rows and columns, forming non-overlapping windows and extracting statistical features. Co-occrance based statistical technique is used for extracting four prominent texture features from an image. Stage two includes, feeding of these parameters to Multi-Layer Perceptron (MLP) as input and output. Hidden layer output was treated as characteristics of the patterns and fed to classifier to classify into six different classes. Graphical user interface was designed to pose a query of texture pattern and retrieval results are shown. © 2012 Springer-Verlag.

Communications in Computer and Information Science

Texture feature extraction and classification by combining statistical and neural based technique for efficient CBIR

The Network performance optimization, configuration depends on proper design of complete network. The network layer is primarily concerned with routing. The packets may cross many networks to reach the destination during this process. To achieve its goals, the network layer must know about the topology, communication subnets and the version of the IP addresses used. The present version of IP is version 4 which must communicate with the next generation of IP addresses which is version 6. As both the versions of Internet Protocol must co-exist, we need some mechanisms that can help the transition process run smoothly. The old applications which are still using IP v4 should work smoothly with IP v6. We discuss IPv6 secure tunneling mechanism that has some advantages over the other models. The model discussed here can be used to establish hybrid communications between the two different versions of Internet protocol in both ways. Copyright 2012 ACM.

ACM International Conference Proceeding Series

IP V6 secure tunneling mechanism

A vision-based driver assistance system using image processing technology consists of three main modules: road detection, traffic sign detection/identification, obstacle detection. Traffic Sign Recognition is an upcoming research field under applied Computer Vision and Machine Learning which deals with the automatic detection and classification of traffic signs in traffic scene images. In the current paper, we discuss the methodology used to detect the road sign from a traffic sign scene image and present a technique that can be used to construct a system that recognizes road signs in images. Such a system will ensure that each driver is aware of the rules &amp; hazards on the road &amp; will thus help in improving road safety. Also, the location of the road sign in the traffic sign image is unknown. Once these obstacles are overcome, such a system could be integrated in a Driver Assistance System. The primary objective is to develop an algorithm, which will identify various types of road signs from streaming video of real time road scenes in a reasonable time frame. The algorithm has two main parts: the first one, detection which uses the color and shape information to detect a road sign in a traffic scene picture. The second one, prediction &amp; classification based on Neural Network concept. Our algorithm proposes a variety of MATLAB Image Processing Toolbox commands to determine if a road sign is present in current image. If present, the sign is resized and certain features from the Region of Interest (RoI) are fed as a feature vector to a neural net. This trained Neural Classifier then predicts the class of the road sign. Genetic Algorithms (GA) with built-in intelligence could be incorporated into the current system which will try to look for traffic signs only in environments where there is probability of finding/ detecting one. Copyright 2012 ACM.

Neural network based smart vision system for driver assistance in extracting traffic signposts

Association rule mining is used to uncover closely related item sets in transactions for deciding business policies. Apriori algorithm is widely adopted is association rule mining for generating closely related item sets. Traditional apriori algorithm is space and time consuming since it requires repeated scanning of whole transaction database. In this paper we propose improved apriori algorithm based on compressed transaction database. Transaction database is compressed based on the consequence of interest. © 2012 IEEE.