Current Issue : October - December Volume : 2017 Issue Number : 4 Articles : 5 Articles
Homomorphic encryption can protect user�s privacy when operating on user�s data in cloud computing. But it is not practical for\nwide using as the data and services types in cloud computing are diverse. Among these data types, digital image is an important\npersonal data for users. There are also many image processing services in cloud computing. To protect user�s privacy in these\nservices, this paper proposed a scheme using homomorphic encryption in image processing. Firstly, a secret key homomorphic\nencryption (IGHE) was constructed for encrypting image. IGHE can operate on encrypted floating numbers efficiently to adapt to\nthe image processing service. Then, by translating the traditional image processing methods into the operations on encrypted pixels,\nthe encrypted image can be processed homomorphically. That is, service can process the encrypted image directly, and the result\nafter decryption is the same as processing the plain image. To illustrate our scheme, three common image processing instances were\ngiven in this paper. The experiments show that our scheme is secure, correct, and efficient enough to be used in practical image\nprocessing applications....
Exploiting the Bachet weight decomposition theorem, a new two-dimensional filter is\ndesigned. The filter can be adapted to different multimedia applications, but in this work it is\nspecifically targeted to image processing applications. The method allows emulating standard\n32 bit floating point multipliers using a chain of fixed point adders and a logic unit to manage the\nexponent, in order to obtain IEEE-754 compliant results. The proposed design allows more compact\nimplementation of a floating point filtering architecture when a fixed set of coefficients and a fixed\nrange of input values are used. The elaboration of the data proceeds in raster-scan order and is capable\nof directly processing the data coming from the acquisition source thanks to a careful organization of\nthe memories, avoiding the implementation of frame buffers or any aligning circuitry. The proposed\narchitecture shows state-of-the-art performances in terms of critical path delay, obtaining a critical\npath delay of 4.7 ns when implemented on a Xilinx Virtex 7 FPGA board....
Automated human emotion detection is a topic of significant interest in the field of computer vision. Over the past\ndecade, much emphasis has been on using facial expression recognition (FER) to extract emotion from facial\nexpressions. Many popular appearance-based methods such as local binary pattern (LBP), local directional pattern\n(LDP) and local ternary pattern (LTP) have been proposed for this task and have been proven both accurate and\nefficient. In recent years, much work has been undertaken into improving these methods. The gradient local ternary\npattern (GLTP) is one such method aimed at increasing robustness to varying illumination and random noise in the\nenvironment. In this paper, GLTP is investigated in more detail and further improvements such as the use of enhanced\npre-processing, a more accurate Scharr gradient operator, dimensionality reduction via principal component analysis\n(PCA) and facial component extraction are proposed. The proposed method was extensively tested on the CK+ and\nJAFFE datasets using a support vector machine (SVM) and shown to further improve the accuracy and efficiency of\nGLTP compared to other common and state-of-the-art methods in literature....
Seamless texture mapping is one of the key technologies for photorealistic 3D texture\nreconstruction. In this paper, a method of rapid texture optimization of 3D urban reconstruction\nbased on oblique images is proposed aiming at the existence of texture fragments, seams, and\ninconsistency of color in urban 3D texture mapping based on low-altitude oblique images. First, we\nexplore implementing radiation correction on the experimental images with a radiation procession\nalgorithm. Then, an efficient occlusion detection algorithm based on OpenGL is proposed according\nto the mapping relation between the terrain triangular mesh surface and the images to implement\nthe occlusion detection of the visible texture on the triangular facets as well as create a list of visible\nimages. Finally, a texture clustering algorithm is put forward based on Markov Random Field utilizing\nthe inherent attributes of the images and solve the energy function minimization by Graph-Cuts.\nThe experimental results display that the method is capable of decreasing the existence of texture\nfragments, seams, and inconsistency of color in the 3D texture model reconstruction....
In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial\nredundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully\nin various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted\nsum of the center pixels of neighboring patches, within a given search window. The weights are based on the patch\nintensity vector distances. The process requires computing vector distances for all of the patches in the search window.\nDirect extension of this method from 2D to 3D, for video processing, can be computationally demanding. Note that\nthe size of a 3D search window is the size of the 2D search window multiplied by the number of frames being used to\nform the output. Exploiting a large number of frames in this manner can be prohibitive for real-time video processing.\nHere, we propose a novel recursive NLM (RNLM) algorithm for video processing. Our RNLM method takes advantage\nof recursion for computational savings, compared with the direct 3D NLM. However, like the 3D NLM, our method is\nstill able to exploit both spatial and temporal redundancy for improved performance, compared with 2D NLM. In our\napproach, the first frame is processed with single-frame NLM. Subsequent frames are estimated using a weighted sum\nof pixels from the current frame and a pixel from the previous frame estimate. Only the single best matching patch\nfrom the previous estimate is incorporated into the current estimate. Several experimental results are presented here\nto demonstrate the efficacy of our proposed method in terms of quantitative and subjective image quality....
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