National Institute of Technology, Silchar

About: National Institute of Technology, Silchar is a education organization based out in Silchar, Assam, India. It is known for research contribution in the topics: Computer science & Control theory. The organization has 1934 authors who have published 4219 publications receiving 41149 citations. The organization is also known as: NIT Silchar.

Comprehensive Seismicity, Seismic Sources and Seismic Hazard Assessment of Assam, North East India

Abstract: In this study, an effort has been made to perform seismic hazard analysis (SHA) for the state of Assam, considering earthquake catalog collected since 1761–2015 using PSHA and DSHA methods at bed r...

Computer-aided detection and diagnosis of mammographic masses using multi-resolution analysis of oriented tissue patterns

Abstract: In this article, a novel approach is proposed for automatic detection and diagnosis of mammographic masses, one of the common signs of non-palpable breast cancer. However, detection and diagnosis of mass are difficult due to its irregular shape, variability in size, and occlusion within breast tissue. The main aim of this study is to classify masses into benign and malignant after detecting them automatically. We propose an iterative method of high-to-low intensity thresholding controlled by radial region growing for the detection of masses. Based on the observation that in presence of mass orientation of tissue patterns changes, which may differ from benign to malignant, a multi resolution analysis of orientation of tissue patterns is then performed to categorize them. The performance of the proposed algorithm is evaluated with images from the digital database for screening mammography (DDSM), containing 450 benign masses, 440 malignant masses, and 410 normal images. A sensitivity of 85.0% is achieved at 1.4 false positives per image in mass detection, whereas an area under the receiver operating characteristic curve of 0.92 with an accuracy of 83.30% is achieved for the diagnosis of malignant masses.

Geometric distortion correction based robust watermarking scheme in LWT-SVD domain with digital watermark extraction using SVM

Abstract: With the advent of technology, digital image watermarking turns to be an effective technique to protect digital images from illegal usages and manipulation. In digital image watermarking, one of the major challenges is to provide robustness against geometrical attack maintaining adequate level of imperceptibility and security. In this work, a robust digital image watermarking scheme is proposed based on the combination of lifting wavelet transform(LWT) and singular value decomposition(SVD). To achieve better correlation between the extracted and original watermark, SVM-based binary classification approach is integrated in watermark extraction. In the proposed technique, geometric distortion correction based approach is incorporated with SVM based binary watermark detection to achieve improved robustness against de-synchronization attack. The 3-level LWT is performed on the cover image where horizontal (HL) sub-band is chosen for binary watermark insertion. The training and testing patterns are formed using an optimized set of features along with the singular values of corresponding blocks. In case of de-synchronization attacks, geometrical distortion correction is required before performing watermark extraction. In the detection process, the geometric distortion parameters of the attacked watermarked image are estimated by the geometric correction method. This algorithm provides high robustness against both the geometrical and non-geometrical attacks. It has been observed that the algorithm gives average imperceptibility of ~42.27 dB with the watermark capacity of 512 bits. Experimental results suggest that the proposed watermarking scheme provides significant improvement in terms of robustness and security of the watermark. The subjective analysis also suggests that proposed scheme provides improved performance over some of the recent existing techniques.