Topic
Feature hashing
About: Feature hashing is a research topic. Over the lifetime, 993 publications have been published within this topic receiving 51462 citations.
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01 Apr 2008
TL;DR: A geometric hash function able to cluster similar shapes and its use for symbol spotting in technical documents is presented and this hashing technique aims to perform a fast spotting process to find candidate locations needing neither a previous segmentation step nor a priori knowledge or learning step involving multiple instances of the object to recognize.
Abstract: In this paper a geometric hash function able to cluster similar shapes and its use for symbol spotting in technical documents is presented. A very compact representation of features describing each primitive composing a symbol are used as key indexes of a hash table. When querying a symbol in this indexing table a voting scheme is used to validate the hypothesis of where this symbol is likely to be found. This hashing technique aims to perform a fast spotting process to find candidate locations needing neither a previous segmentation step nor a priori knowledge or learning step involving multiple instances of the object to recognize.
15 citations
21 Feb 1989
TL;DR: An O(n3) algorithm that has been applied to building hash functions for a collection of 69806 words on a CD-ROM and a much better algorithm is developed and a perfect hash function is found for a set of 130,199 words taken from sources including the Collins English Dictionary.
Abstract: As the use of knowledge-based systems increases, there will be a growing need for efficient artificial intelligence systems and methods to access large lexicons. In the COmposite Document Expert/extended/effective Retrieval (CODER) system we have, in order to provide rapid access to data items on CD-ROMs and to terms in a lexicon built from machine readable dictionaries, investigated the construction of perfect hash functions. We have considered algorithms reported earlier in the literature, have made numerous enhancements to them, have developed new algorithms, and here report on some of our results. This paper covers an O(n3) algorithm that has been applied to building hash functions for a collection of 69806 words on a CD-ROM. Most recently we have developed a much better algorithm and have succeeded in finding a perfect hash function for a set of 130,199 words taken from sources including the Collins English Dictionary.
15 citations
TL;DR: Performance of the proposed hashing method is evaluated with an important application in perceptual image hashing scheme: image authentication and experiments are conducted to show that the present method has acceptable robustness against perceptual content-preserving manipulations.
Abstract: Feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. Simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of Local Binary Pattern features. In this paper, we investigate the use of local binary patterns for perceptual image hashing. In feature extraction, we propose to use both sign and magnitude information of local differences. So, the algorithm utilizes a combination of gradient-based and LBP-based descriptors for feature extraction. To provide security needs, two secret keys are incorporated in feature extraction and hash generation steps. Performance of the proposed hashing method is evaluated with an important application in perceptual image hashing scheme: image authentication. Experiments are conducted to show that the present method has acceptable robustness against perceptual content-preserving manipulations. Moreover, the proposed method has this capability to localize the tampering area, which is not possible in all hashing schemes.
15 citations
09 Jul 2012
TL;DR: This work proposes a novel image authentication system by combining perceptual hashing and robust watermarking, and significantly outperforms a state-of-the-art algorithm.
Abstract: We propose a novel image authentication system by combining perceptual hashing and robust watermarking. An image is divided into blocks. Each block is represented by a compact hash value. The hash value is embedded in the block. The authenticity of the image can be verified by re-computing hash values and comparing them with the ones extracted from the image. The system can tolerate a wide range of incidental distortion, and locate tampered areas as small as $1/64$ of an image. In order to have minimal interference, we design both the hash and the watermark algorithms in the wavelet domain. The hash is formed by the sign bits of wavelet coefficients. The lattice-based QIM watermarking algorithm ensures a high payload while maintaining the image quality. Extensive experiments confirm the good performance of the proposal, and show that our proposal significantly outperforms a state-of-the-art algorithm.
15 citations
09 Jan 2007
TL;DR: This paper presents a novel hashing scheme that is resilient to allow non-malicious manipulations like JPEG compression, high pass filtering and is sensitive enough to detect tampering with precise localization.
Abstract: The purpose of an image hash is to provide a compact representation of the whole image. Designing a good image hash function requires careful consideration of many issues such as robustness, security and tamper detection with precise localization. In this paper, we present a novel hashing scheme that addresses these issues in a unified framework. We analyze the security issues in image hashing and present new ideas to counter some of the attacks that we shall describe in this paper. Our proposed scheme is resilient to allow non-malicious manipulations like JPEG compression, high pass filtering and is sensitive enough to detect tampering with precise localization. Several experimental results are presented to demonstrate the effectiveness of the proposed scheme.
14 citations