Department of Computer Science & Engineering

&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

This paper presents a multimodal biometric fusion algorithm that supports biometric image quality and case-based context switching approach for selecting appropriate constituent unimodal traits and fusion algorithms. Depending on the quality of input samples, the proposed algorithm intelligently selects appropriate fusion algorithm for optimal performance. Experiments and correlation analysis on a multimodal database of 320 subjects show that the context switching algorithm improves the verification performance both in terms of accuracy and time. © 2009 Springer-Verlag Berlin Heidelberg.

World University root node

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Context switching algorithm for selective multibiometric fusion

Existing algorithms that fuse level-2 and level-3 fingerprint match scores perform well when the number of features are adequate and the quality of images are acceptable. In practice, fingerprints collected under unconstrained environment neither guarantee the requisite image quality nor the minimum number of features required. This paper presents a novel fusion algorithm that combines fingerprint match scores to provide high accuracy under non-ideal conditions. The match scores obtained from level-2 and level-3 classifiers are first augmented with a quality score that is quantitatively determined by applying redundant discrete wavelet transform to a fingerprint image. We next apply the generalized belief functions of Dezert-Smarandache theory to effectively fuse the quality-augmented match scores obtained from level-2 and level-3 classifiers. Unlike statistical and learning based fusion techniques, the proposed plausible and paradoxical reasoning approach effectively mitigates conflicting decisions obtained from classifiers especially when the evidences are imprecise due to poor image quality or limited fingerprint features. The proposed quality-augmented fusion algorithm is validated using a comprehensive database which comprises of rolled and partial fingerprint images of varying quality with arbitrary number of features. The performance is compared with existing fusion approaches for different challenging realistic scenarios. © 2008 Elsevier Inc.

Fulltext

International Journal of Approximate Reasoning

Quality-augmented fusion of level-2 and level-3 fingerprint information using DSm theory

This paper presents an algorithm for medical 3D image denoising and segmentation using redundant discrete wavelet transform. First, we present a two stage denoising algorithm using the image fusion concept. The algorithm starts with globally denoising the brain images (3D volume) using Perona Malik's algorithm and RDWT based algorithms followed by combining the outputs using entropy based fusion approach. Next, a region segmentation algorithm is proposed using texture information and k-means clustering. The proposed algorithms are evaluated using brain 3D image/volume data. The results suggest that the proposed algorithms provide improved performance compared to existing algorithms.

Proceedings of the 2009 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2009

Denoising and segmentation of 3D brain images

This paper presents a fast fingerprint verification algorithm using level-2 minutiae and level-3 pore and ridge features. The proposed algorithm uses a two-stage process to register fingerprint images. In the first stage, Taylor series based image transformation is used to perform coarse registration, while in the second stage, thin plate spline transformation is used for fine registration. A fast feature extraction algorithm is proposed using the Mumford-Shah functional curve evolution to efficiently segment contours and extract the intricate level-3 pore and ridge features. Further, Delaunay triangulation based fusion algorithm is proposed to combine level-2 and level-3 information that provides structural stability and robustness to small changes caused due to extraneous noise or non-linear deformation during image capture. We define eight quantitative measures using level-2 and level-3 topological characteristics to form a feature supervector. A 2 ν-support vector machine performs the final classification of genuine or impostor cases using the feature supervectors. Experimental results and statistical evaluation show that the feature supervector yields discriminatory information and higher accuracy compared to existing recognition and fusion algorithms.

Signal Processing

Combining pores and ridges with minutiae for improved fingerprint verification

The Ka band regenerative payload is a transponder of GSAT-4 satellite [1]. It provides Narrow Spot Beams, Wide Bandwidth and small size of antenna for both transmission and reception. The Signaling Demodulator is a one of the important subsystem of regenerative Payload. This Signaling Demodulator was developed in-house for providing signaling information to provide communication between one spot beam to other. The demodulator software was developed for functionality of getting the signaling request from the user terminal & the processing of the request onboard.

2009 International Conference on Emerging Trends in Electronic and Photonic Devices and Systems, ELECTRO '09

Design, implementation and realization of 64Kbps 1/2 QPSK based burst demodulator for onboard application

Advances and Applications of DSmT for Information Fusion

Framework for biometric match score fusion using statistical and belief models

INDIAN JOURNAL OF PHARMACEUTICAL SCIENCES

Restructuring Pharmaceutical Education for Next Generation Pharmacist : A Survey Report

We perform a combinatorial analysis of the SHA-2 compression function. This analysis explains in a unified way the recent attacks against reduced round SHA-2. We start with a general class of local collisions and show that the previously used local collision by Nikolić and Biryukov (NB) and Sanadhya and Sarkar (SS) are special cases. The study also clarifies several advantages of the SS local collision over the NB local collision. Deterministic constructions of up to 22-round SHA-2 collisions are described using the SS local collision and up to 21-round SHA-2 collisions are described using the NB local collision. For 23 and 24-round SHA-2, we describe a general strategy and then apply the SS local collision to this strategy. The resulting attacks are faster than those proposed by Indesteege et al using the NB local collision. We provide colliding message pairs for 22, 23 and 24-round SHA-2. Although these attacks improve upon the existing reduced round SHA-256 attacks, they do not threaten the security of the full SHA-2 family. 1 © 2009 Springer Science + Business Media, LLC.

Cryptography and Communications

A combinatorial analysis of recent attacks on step reduced SHA-2 family

In this paper we present a novel shape descriptor based on shape context, which in combination with hierarchical distance based hashing is used for word and graphical pattern based document image indexing and retrieval. The shape descriptor represents the relative arrangement of points sampled on the boundary of the shape of object. We also demonstrate the applicability of the novel shape descriptor for classification of characters and symbols. For indexing, we provide a new formulation for distance based hierarchical locality sensitive hashing. Experiments have yielded promising results. © 2009 IEEE.

Proceedings of the International Conference on Document Analysis and Recognition, ICDAR

Shape descriptor based document image indexing and symbol recognition

Visual sensor network design facilitates applications such as intelligent rooms, video surveillance, automatic multicamera tracking, activity recognition etc. These applications require an efficient visual sensor layout which provides a minimum level of image quality or image resolution. This paper addresses the practical problem of optimally placing the multiple PTZ cameras to ensure maximum coverage of user defined priority areas with optimum values of parameters like pan, tilt, zoom and the locations of the cameras. The proposed algorithm works offline and does not require camera calibration. We mapped this problem as an optimization problem using Genetic Algorithm, by defining, coverage matrix as a set of sensor parameters and the space model parameters like priority areas, obstacles and feasible locations of the sensors, and by modelling discrete spaces using probabilistic frame work. We minimized the probability of occlusion due to randomly moving objects by covering each priority area using multiple cameras. The proposed method will be applicable for surveillance of large spaces with discrete priority areas like a hall with more than one entrance or many events happening at different locations in a hall eg.Casino. As we are optimizing the parameters like pan, tilt, zoom and even the locations of the cameras, the coverage provided by this approach will assure good resolution, which improves the QOS of the visual sensor network. © 2009 IEEE.