Informatics Publishing Limited

M. Mohammed Sathik ¹, S. S. Sujatha ²

Affiliations
1 Department of Computer Science, Sadakathullah Appa College, Tirunelveli, TamilNadu, IN
2 Department of Computer Science, S T Hindu College, Nagercoil, Tamilnadu, IN

Abstract

This paper proposes an algorithm that embeds the watermark information in host image in order to authenticate it.  The input image is divided into non overlapping blocks and a matrix pattern is derived from the pixel values of those blocks. A watermark is obtained by scrambling the matrix pattern with Arnold Transform. The constructed watermark is embedded within the host image. The operation of embedding and extraction of watermark is done in high frequency domain of Discrete Wavelet Transform. This watermarking scheme deals with the extraction of the watermark information in the absence of original image. The proposed method is checked for different noise attacks like salt & pepper and Gaussian, median filtering and image adjustment. Peak Signal to Noise Ratio (PSNR) is computed to measure image quality. The proposed method exhibits high security and high imperceptibility features.

 

Keywords

Arnold Transform, Content Based Watermarking, Digital Watermarking, Discrete Wavelet Transform, Image Authentication.

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A. A. Haseena Thasneem ¹, R. Mehaboobathunnisa ¹, M. Mohammed Sathik ¹, S. Arumugam ²

Affiliations
1 Department of Computer Science, Sadakathullah Appa College, IN
2 Nandha Engineering College, IN

Abstract

This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive), Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging), Contour models (Active Contour Model and Chan - Vese Model) and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.

Keywords

Thresholding, Expectation Maximization, Contour Models, Dermoscopy, Spectral Clustering.

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