Robust and secure perceptual image hashing in the transform domain

The rapid development of multimedia devices such as computers, network technologies, and cell phones have made it easier for users to create, broadcast, convey, share, store, and distribute multimedia data including images, videos and audio files on a daily basis. However, the availability of image processing software in the public domain has facilitated illegal copying and distribution of digital images with unnoticeable quality changes. Thus, security and identification of media content has become an important and demanding area for research. Perceptual hashing is one of the recent technologies used for multimedia content security. A perceptual image hash function is a hash function that is robust against content-preserving operations (CPOs), such as noise, JPEG lossy compression and rotation. This aim of this research is to study and investigate existing techniques and then contribute to the development of new perceptual image hashing techniques in the transform domain for image identification and copy detection applications. The design requirements for any perceptual image hashing system are robustness, discriminative capability (uniqueness), and unpredictability (security). The feature extraction stage plays a key role in ensuring the system output is robust and discriminative. This thesis mainly focuses on the robust feature extraction stage and the analysis of the proposed system’s security. The following contributions have been made: A new perceptual hashing technique using pseudo-random sub-images in the discrete wavelet transform (DWT) domain for extracting features has been developed. The idea employs a recent dimension reduction technique, referred to as non-negative matrix factorization (NMF) in the literature, for enhancing the robustness and security of the hash. This approach is proposed to select the most stable coefficients under various content-preserving operations, compact. The robust image hashes are generated by applies DWT and NMF into image. The proposed sub-images-DWT technique has been shown to yield good performance under image processing operations, but it still suffers from geometric attacks. A new rotation-invariant FMT-based hashing technique incorporating the Fourier-