Aneka- Detecting various forms of the same Wavelet Image Hashing Algorithm

Abstract

Digital imaging has experienced tremendous growth in recent decades, and have been used in a growing number of applications. With such increasing popularity and the availability of low-cost image editing software, the integrity of digital image content can no longer be taken for granted. This thesis introduces a new methodology for the forensic analysis of digital images. It proposes a novel hashing method using scale-invariant feature transform (SIFT) features points and Discrete Wavelet Transform (DWT) approximation coefficients for image authentication. Experimental results show that the proposed method is robust to various content-preserving operations. In addition, the performance of the proposed method is compared to existing methods. The comparison results show that the proposed method performs better than the existing methods. This thesis also mentions about the Amazon Web Services that are being used in detail. Also, the name of this thesis — Aneka means that which have many variations. This thesis also talks about recognizing nearly duplicate/similar images or detecting differents variations of an image present in a database. Aneka is also one of the names of Lord Vishnu.