A Review of Hashing based Image Copy Detection Techniques <s> Introduction <s> This paper describes RIME (Replicated IMage dEtector), an alternative approach to watermarking for detecting unauthorized image copying on the Internet. RIME profiles internet images and stores the feature vectors of the images and their URLs in its repository. When a copy detection request is received, RIME matches the requested image's feature vector with the vectors stored in the repository and returns a list of suspect URLs. RIME characterizes each image using Daubechies' wavelets. The wavelet coefficients are stored as the feature vector. RIME uses a multidimensional extensible hashing scheme to index these high-dimensional feature vectors. Our preliminary result shows that it can detect image copies effectively: It can find the top suspects and copes well with image format conversion, resampling, and requantization. <s> BIB001 </s> A Review of Hashing based Image Copy Detection Techniques <s> Introduction <s> In 2003, Kim applied the discrete cosine transform (DCT) technique to propose a content-based image copy detection method. He successfully detected the copies both with and without modifications, and his method is the first to detect the copies with water coloring and twirling modifications. However, Kim's method can only detect copies having a 180^o rotation. When copies have a 90^o or 270^o rotation, Kim's method fails to discover them. Also, his method cannot deal with copies having only minor rotations of 1^o or 5^o, and so on. To conquer this weakness, we propose an elliptical track division strategy to extract two kinds of features in the design of our proposed methods. Furthermore, we propose a dynamic center point detection mechanism for the elliptical track of each image to deal with the shifting process. The experimental results confirm that both proposed methods can successfully capture the features of an image even if it is shifted, cropped or rotated to any degree. In addition, our hybrid method can further provide accurate detection performance for a variety of manipulations. <s> BIB002 </s> A Review of Hashing based Image Copy Detection Techniques <s> Introduction <s> Copy detection aims to identify various content-preserving copies from the same origin and distinguish the different sources. In this paper, we propose a novel feature for image copy detection based on the radon transform (RT). We first theoretically analyze that the proposed feature is invariant against rotation, scaling and translation (RST) operations and robust to lossy JPEG compression and additive noises. The feature can meet the robustness requirements of copy detection applications. The proposed feature is statistically dependent of image content and is capable of capturing unique information of the image for fragility of the copy detection system. The experimental results show that the proposed scheme outperforms the existing methods, when detecting image copies subjected to various transformations, in terms of receiver operating characteristic (ROC) curves. <s> BIB003 </s> A Review of Hashing based Image Copy Detection Techniques <s> Introduction <s> Region-duplication forgery is one of most common tampering artifices. Several methods have been developed to detect and locate the tampered region, while most methods do fail when the copied region is rotated before being pasted because of the de-synchronization in the searching procedure. To solve the problem, the paper proposes an efficient and robust passive authentication method that uses the circle block and the Hu moments to detect and locate the duplicate regions with rotation. Experimental results show that our method is robust not only to noise contamination, blurring and JPEG compression, but also to the rotation. Meanwhile, the proposed method has better time performance compared with exiting methods because of the lower feature dimension. <s> BIB004 </s> A Review of Hashing based Image Copy Detection Techniques <s> Introduction <s> Abstract Conventional image hash functions only exploit luminance components of color images to generate robust hashes and then lead to limited discriminative capacities. In this paper, we propose a robust image hash function for color images, which takes all components of color images into account and achieves good discrimination. Firstly, the proposed hash function re-scales the input image to a fixed size. Secondly, it extracts local color features by converting the RGB color image into HSI and YCbCr color spaces and calculating the block mean and variance from each component of the HSI and YCbCr representations. Finally, it takes the Euclidian distances between the block features and a reference feature as hash values. Experiments are conducted to validate the efficiency of our hash function. Receiver operating characteristics (ROC) curve comparisons with two existing algorithms demonstrate that our hash function outperforms the assessed algorithms in classification performances between perceptual robustness and discriminative capability. <s> BIB005 </s> A Review of Hashing based Image Copy Detection Techniques <s> Introduction <s> Abstract Medical volume data containing patient information is often faced with various attacks in the transmission process. In order to enhance the medical information system security, and effectively solve the problem of medical volume data protection, a new zero-watermarking algorithm is proposed in the paper. The new zero-watermarking algorithm takes advantage of three-dimensional discrete wavelet transform multi-resolution analysis characteristics of space and time, threedimensional discrete cosine transform properties, and differences hashing robust characteristic. In order to enhance watermarking algorithm security, Legendre chaotic neural network is used for scrambling original watermark image. The medical volume data is made by three-dimensional discrete wavelet transform, threedimensional discrete cosine transform and three-dimensional discrete inverse cosine transform r to obtain the medical volume data feature matrix 4×5×4, which is converted to 64-bit binary feature sequence through difference hashing algorithm. The 64-bit binary feature sequence is used to construct the zero-watermarking. The experimental results prove that the new zero-watermarking has favorable security and robustness resisting various attacks. Therefore, the new zero-watermarking algorithm is more applicable to protect medical volume data. <s> BIB006
The unauthorized generation of duplicate multimedia content has always been far ahead of sophisticated copy detection techniques   . Various easy to use image processing software's can do manipulations in the original images BIB004 and consequently it is very common to find the number of unauthorized duplicate copies of an original image. These duplicated images may have the same visual content as the original image, but their digital representations may be different. Due to this easy to copy nature of images, it is important to protect the copyright of an image [4] and therefore the identification of duplicate copies of an image is an important issue of digital rights management  . In many circumstances, it becomes imperative that the authenticity of the image must be verified before it is accepted. Image authentication techniques are used to prove that a received image is original and is not a duplicate copy  . This put us in the area of Image forensics  , which uses a number of techniques not only to verify the authenticity of an image but also to detect unauthorized copies. One of the most commonly used approaches in Image forensics is digital watermarking. In general, watermarking can be considered as the introduction of a signature, within an image before it is distributed [4] and its ownership can then be determined by verifying the signature BIB006 . A significant drawback of this scheme is that applying one or more image processing operations can easily distort or even destroy the watermark. Secondly, certain applications do not permit the embedding of a watermark since it usually leads to irreversible changes within the image, which may not be perceptual. In addition, watermark-based systems are rendered ineffective if the original image is disseminated before embedding the watermark, which might be the case in most situations. In such a situation, we require techniques that can address the drawbacks of watermarking techniques BIB002 . Content-based image copy detection is an image forensic technique that has gathered attention from researchers as an alternative to digital watermarking BIB001  . Unlike watermarking, content-based copy detection techniques do not depend on embedding any mark within the image instead, the characteristics of the multimedia content itself can be used to identify its ownership  . The basic idea of image copy detection lies in extracting a unique image-based feature, which can be used to represent the entire image  . To verify the authenticity of the received image, the same set of features are extracted from both the original and the received image and compared  . Copy detection techniques are usually designed to be robust against image processing attacks and hence are preferred over other techniques used for image ownership and identification BIB003 . The applications of copy detection include authentication, usage tracking, copyright violation enforcement, etc. As an example, consider the three images shown in Fig. 1 . The image shown in Fig. 1b is a copy of the image shown in Fig. 1a as it has been obtained by applying an image processing function. However, the image shown in Fig. 1c is a different image and is not a copy of either Fig. 1a or b, though perceptually similar  . For this example, a perfect image copy detection mechanism should detect image 1b as a copy of image 1a and treat image 1c as a different image  . More recently, researchers have begun to focus on hashing-based image copy detection techniques, which is the next logical step after content-based image copy detection [18, BIB005 . This paper, therefore, provides a comprehensive review of the state-of-the-art hashing-based image copy detection techniques. The reviewed techniques are compared by using different performance parameters to provide an overview of best-performing hashing based copy detection technique. Rest of the paper is organized as follows: Section 2 gives the general scenario of hashing-based image copy detection system. Section 3 reviews various hashingbased image copy detection algorithms. Section 4 gives the various functional blocks used within the reviewed algorithms. Performance evaluation parameters are discussed in Section 5. Section 6 presents a comparison of the state-of-art techniques. Section 7 finally presents discussion and conclusions.