Neighborhood Discriminant Hashing for Large-Scale Image Retrieval

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval With the proliferation of large-scale community contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample…

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Lossless and Reversible Data Hiding in Encrypted Images with Public Key Cryptography

Lossless and Reversible Data Hiding in Encrypted Images with Public Key Cryptography Circuits and Systems for Video Technology A lossless, a reversible, and a combined data hiding schemes is proposed for ciphertext images encrypted by public key cryptosystems with probabilistic and homomorphic properties. In the lossless scheme, the ciphertext pixels are replaced with new values to embed the additional data into several LSB-planes of ciphertext pixels by multi-layer wet paper coding. Then, the embedded data can be directly extracted from the encrypted domain, and the data embedding operation does not…

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Towards Large-Scale Histopathological Image Analysis: Hashing-Based Image Retrieval

Towards Large-Scale Histopathological Image Analysis: Hashing-Based Image Retrieval Automatic analysis of histopathological images has been widely utilized leveraging computational image-processing methods and modern machine learning techniques. Both computer- aided diagnosis (CAD) and content-based image-retrieval (CBIR) systems have been successfully developed for diagnosis, disease detection, and decision support in this area. Large-scale and data-driven methods have emerged to offer a promise of bridging the semantic gap between images and diagnostic information. Scalable image-retrieval technique is developed to cope intelligently with massive histopathological images. Specifically, a supervised kernel hashing technique is proposed,…

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Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation

Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation JAVA Technology Information Forensics and Security Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation In many practical scenarios, image encryption has to be conducted prior to image compression. This has led to the problem of how to design a pair of image encryption and compression algorithms such that compressing the encrypted images can still be efficiently performed. In this paper, we design a highly efficient image encryption-then-compression (ETC) system, where both lossless…

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Hierarchical Prediction and Context Adaptive Coding for Lossless Color Image Compression

Hierarchical Prediction and Context Adaptive Coding for Lossless Color Image Compression This paper presents a new lossless color image compression algorithm, based on the hierarchical prediction and context-adaptive arithmetic coding. For the lossless compression of an RGB image, it is first decorrelated by a reversible color transform and then Y component is encoded by a conventional lossless grayscale image compression method. For encoding the chrominance images, we develop a hierarchical scheme that enables the use of upper, left, and lower pixels for the pixel prediction, whereas the conventional raster scan…

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Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering

Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation Image encryption has to be conducted prior to image compression in many applications. This has led to the problem of how to design a pair of image encryption and compression algorithms such that compressing the encrypted images can still be efficiently performed. In this paper, we design a highly efficient image encryption-then-compression (ETC) system, where both lossless and lossy compression are considered. The proposed image encryption scheme operated in the prediction error domain is shown to be…

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Fingerprint Compression Based on Sparse Representation

Fingerprint Compression Based on Sparse Representation A new fingerprint compression algorithm based on sparse representation is introduced. Obtaining an overcomplete dictionary from a set of fingerprint patches allows us to represent them as a sparse linear combination of dictionary atoms. In the algorithm, we first construct a dictionary for predefined fingerprint image patches. For a new given fingerprint images, represent its patches according to the dictionary by computing l0-minimization and then quantize and encode the representation. In this paper, we consider the effect of various factors on compression results. Three…

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Sketch4match Content-based image retrieval system using sketches

Sketch4match Content-based image retrieval system using sketches The content based image retrieval (CBIR) is one of the most popular, rising research areas of the digital image processing. Most of the available image search tools, such as Google Images and Yahoo! Image search, are based on textual annotation of images. In these tools, images are manually annotated with keywords and then retrieved using text-based search methods. The performances of these systems are not satisfactory. The goal of CBIR is to extract visual content of an image automatically, like color, texture, or…

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Local Directional Number Pattern for Face Analysis: Face and Expression Recognition

Local Directional Number Pattern for Face Analysis: Face and Expression Recognition Technology Used: Dot Net This paper proposes a novel local feature descriptor, local directional number pattern (LDN), for face analysis, i.e., face and expression recognition. LDN encodes the directional information of the face’s textures (i.e., the texture’s structure) in a compact way, producing a more discriminative code than current methods. We compute the structure of each micro-pattern with the aid of a compass mask that extracts directional information, and we encode such information using the prominent direction indices (directional numbers) and…

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