Robust image hashing
WebJun 2, 2024 · Third, a robust image hashing construction method is proposed by utilizing the Horizontal Location-Context Hashing (HLCH) and Vertical Location-Context Hashing (VLCH) method, which encoding the geometric distribution and image content together. WebRobust images hashing has been extensively studied for content-based identi cation of 2D images. Generally, image hashing consists of two main aspects, one is feature extraction, and the other is feature compression. Since feature extraction can directly a ect the robustness and discrimination performance of image hashing, more and more
Robust image hashing
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Weba mesh-based media hash-dependent image watermarking scheme that can achieve blind detection and has been veri-fied to be robust against signal processing attacks. Accord-ing to this study, our observations are summarized as fol-lows: (1) the common use of cryptographic hashing found in the literature is not suitable for both owners (due ot its WebSep 12, 2014 · Robust image hashing is an effective technique to help identifying known illegal images even after the original images were modified by applying various image processing operations. However, some specific operations lead to increased false negative rates when using robust image hashing. One of the most challenging operations today is …
WebJul 27, 2005 · Image hashes based on wavelet coefficients were proposed in [363,383]. In particular, Yang and Chen [383] proposed a method for robust image hashing based on … WebJun 5, 2006 · Robust and secure image hashing Abstract: Image hash functions find extensive applications in content authentication, database search, and watermarking. This paper develops a novel algorithm for generating an image hash based on Fourier transform features and controlled randomization.
WebJul 20, 2024 · This work proposes an image hashing algorithm based on cool and warm hue information and the space angle. This algorithm extracts the features of cool and warm … WebAug 1, 2024 · This algorithm is robust against JPEG compression, Gaussian filtering, average filtering and scaling, but is also sensitive to image rotation. (2) Image hashing …
WebOct 1, 2015 · Robustness and discrimination are two of the most important objectives in image hashing. We incorporate ring partition and invariant vector distance to image hashing algorithm for enhancing rotation robustness and discriminative capability. As ring partition is unrelated to image rotation, the statistical features that are extracted from …
WebJun 5, 2006 · Robust and secure image hashing. Abstract: Image hash functions find extensive applications in content authentication, database search, and watermarking. This … o\\u0027reilly benefits hubWebThis thesis mainly focuses on the robust feature extraction stage and the analysis of the proposed system's security, which has been shown that the proposed FMT-based image … roddy mcdowall burial siteWebSep 1, 2024 · The most important properties of the image hashing algorithm are robustness and discrimination [ 9 ]. The requirement of robustness is that the image hashing algorithm must map visually similar images to the same or similar hashes no matter whether their bit representations are the same or not. roddy mcdowall filmographyWebDec 29, 2024 · To address these issues, this paper proposes a new robust image hashing with Isometric Mapping (Isomap) and saliency map for copy detection. A key contribution is hash generation with saliency map determined by the Frequency Tuned (FT) method, which can guarantee robustness of the proposed image hashing. Another contribution is the use … o\\u0027reilly bedford nhWebDec 1, 2024 · A robust image hashing algorithm has three stages: preprocessing, feature extraction, and quantization and coding, as shown in Fig. 2. First, in the preprocessing … o\\u0027reilly benefithubWebContent Based Image Hashing Robust to Geometric Transformations. Authors: Zhang Hanling. View Profile, Xiong Caiqiong. View Profile, Geng Guangzhi ... o\\u0027reilly belfairWebMar 27, 2016 · In other words, image hash should be robust against normal digital processing, such as image compression and image enhancement. (2) Discriminative capability: For different images, image hashing should produce different image hashes. Except these basic properties, image hashing must satisfy other property for some … o\\u0027reilly bellingham