Digital Image Processing

P. Mangaiyarkarasi ¹, S. Arulselvi ¹

Affiliations
1 Department of Instrumentation Engineering, Annamalai University, IN

Abstract

With the increasing use of internet and effortless copying, copyright protection for multimedia data has become an important issue. Digital watermarking has emerged as a tool for protecting the multimedia data from copyright infringement. Many literatures have reported about frequency transform based watermarking techniques for data security, since they are robust against image processing attacks. In this paper, an attempt is made to develop a watermarking scheme based on discrete wavelet transform (DWT) and extraction using fast independent component analysis (FastICA) algorithm. A perceptual model is applied with stochastic approach for watermark embedding. This is based on computation of noise visibility function (NVF) which has local image properties where the strength of watermarking is controlled. ICA, an intelligent detection algorithm, which is based on blind source separation technique, is implemented for extraction without the use of previous knowledge of the original image. The features of FastICA are quick convergence, easy to implement and suitable for watermark applications. Robustness of the proposed scheme is validated by implementing common image processing attacks. Peak signal to noise ratio (PSNR) and similarity measure (SM) values are calculated to evaluate the performance of the proposed work.

Keywords

Discrete Wavelet Transform Independent Component Analysis and Noise Visibility Function.

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G. Thirugnanam ¹, S. Arulselvi ¹

Affiliations
1 Department of Instrumentation Engineering, Annamalai University, Chidambaram, Tamil Nadu, IN

Abstract

With the rapid development of a network multimediaenvironment,digital data can be distributed much faster and easier. To maintain a duplicate of any digital data is easier than before, the enforcement of digital copyright protection is an important issue. In recent years, watermarking has become an emerging area and many watermarking schemes have been proposed for copyright protection. Many literatures have reported about Discrete Wavelet Transform (DWT) and Wavelet Packet Transform (WPT) watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacksand the shift variance of WPT causes inaccurate extraction. In this paper, an attempt is made to develop a watermarking scheme based on Redundant Discrete Wavelet Transform (RDWT) and extraction using Independent Component analysis(ICA). Various ICA like FastICA, Radical ICA, Pearson ICA, Jade ICA, Maximum Likelihood ICA, Mean Field ICA and Kernel ICA are proposed and implemented for extraction. The results reveal that FastICA produces better Similarity Measure and Mutual Information over other ICA methods. To ascertain the effectiveness of proposed technique (RDWT with FastICA), it is implemented for various applications like Medical, Fingerprint and Satellite images. The results are presented and discussed.

Keywords

Copyright Protection, Digital Watermarking, Independent Component Analysis, Redundant Discrete Wavelet Transform.

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R. Thiyagarajan ¹, S. Arulselvi ¹

Affiliations
1 Department of Instrumentation Engineering, Annamalai University, Annamalai Nagar, IN

Abstract

Face recognition is one of the challenging applications of image processing. Robust face recognition algorithm should posses the ability to recognize identity despite many variations in pose, lighting and appearance. Nowadays, Principal Component Analysis (PCA) has been widely adopted as the potential face recognition algorithm. However, it has limitations like poor discriminatory power and large computational load. In view of these limitations, this paper proposes a new approach in using PCA on wavelet sub bands. In the proposed method, wavelet transform is used to decompose an image into different frequency sub bands, and a mid-range frequency sub band is used for PCA representation. In comparison with the conventional use of PCA, the proposed method gives better recognition rate and discriminatory power. Further, the proposed method reduces the computational load significantly even when the image database is large. This paper details the design and implementation of the proposed method, and presents encouraging experimental results with standard Face Database.

Keywords

Human Face Recognition, Principal Component Analysis, Sub Band, Wavelet Transform.

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G. Thirugnanam ¹, S. Arulselvi ¹

Affiliations
1 Dept. of Instrumentation Engineering, Annamalai University, Chidambaram, Tamil Nadu, IN

Abstract

In recent years, watermarking has become an attractive field in the areas like copyright protection, image authentication. Many literatures have reported about Discrete Wavelet Transform (DWT) watermarking techniques for data security. However, DWT based watermarking schemes are found to be less robust against image processing attacks and the shift variance of Wavelet Packet Transform (WPT) causes inaccurate extraction. In this paper, an attempt is made to develop a watermarking scheme based on RDWT and extraction using Independent Component Analysis (ICA). Various ICA like Fast ICA, Radical ICA, Pearson ICA, Jade ICA, Maximum Likelihood ICA, Mean Field ICA and Kernel ICA are proposed and implemented for extraction. Simulation results show that the proposed scheme produces high Peak Signal to Noise Ratio (PSNR) values over other transform techniques like DWT and WPT. Also results reveal that Fast ICA produces better similarity measure and Mutual Information over other ICA methods.

Keywords

Authentication, Digital Watermarking, Independent Component Analysis, Redundant Discrete Wavelet Transform.

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