共查询到20条相似文献,搜索用时 21 毫秒
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Image segmentation is an important step in the implementation of the interpretation of synthetic aperture radar (SAR) image due to speckle. This article proposes a SAR image segmentation method based on perceptual hashing. The new algorithm is divided into two phases. The first phase is to obtain initial regions with multi-thresholding based on histogram after reducing the speckle noise. The initial regions are used as input data. And the next phase is to merge regions according to the similarity between regions. In this phase, to segment SAR image effectively, the proposed hashing algorithm is used to obtain hash value and similarity between regions, which preserve the texture features of SAR images. In addition, we can obtain a smooth segmentation result by reducing the redundant information with principal component analysis. Furthermore, morphological methods are used to eliminate the uneven background in the segmentation results. These improvements make our algorithm more effective to segment the images with high speed. The experimental results of four real and one synthetic SAR images verify the efficiency of our algorithm. 相似文献
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Multimedia Tools and Applications - This paper presents an efficient approach with the reduced length of feature vector for biomedical image retrieval by using global and local features of an... 相似文献
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Multimedia Tools and Applications - Perceptual image hashing finds increasing attention in several multimedia security applications. However, reaching the trade-off balance between the two most... 相似文献
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Roy Moumita Thounaojam Dalton Meitei Pal Shyamosree 《Multimedia Tools and Applications》2022,81(20):29045-29073
Multimedia Tools and Applications - Perceptual image hashing methods utilize the visual phenomenon of the images and produce a fixed-length hash function and this hash value can be utilized for... 相似文献
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Wang Cai-ling Ren Jinchang Wang Hong-wei Zhang Yinyong Wen Jia 《Multimedia Tools and Applications》2018,77(22):29889-29903
Multimedia Tools and Applications - It is of great interest in spectral-spatial features classification for hyperspectral images (HSI) with high spatial resolution. This paper presents a novel... 相似文献
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Gharde Nilesh Dilipkumar Thounaojam Dalton Meitei Soni Badal Biswas Saroj Kr. 《Multimedia Tools and Applications》2018,77(23):30815-30840
Multimedia Tools and Applications - Perceptual image hashing technique uses the appearance of the digital media object as human eye and generates a fixed size hash value. This hash value works as... 相似文献
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在表情识别中Gabor结合局部二值模式(LBP)的特征提取方法以及直方图统计降维虽然是较为局部化的方法,但LBP鲁棒性较差,识别精度不高,而且使用直方图统计来区分表情,其计算复杂度和特征维数依旧较高。中心对称局部二值模式(CS-LBP)与LBP相比具有较好的鲁棒性,但其对表情纹理细节的描述仍不够详细。因此提出基于Gabor结合改进的CS-LBP即二值叠加中心对称局部二值模式(二值叠加CS-LBP)的特征提取方法。用Gabor提取特征,同时用两种计算方式提取两个特征值并叠加,作为最终识别的特征;并通过离散余弦变换(DCT)降维,有效降低表情的特征维数。在JAFFE表情库中实验验证了该方法能有效提高识别精度。 相似文献
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In this paper,we propose a robust perceptual hashing algorithm by using video luminance histogram in shape.The underlying robustness principles are based on three main aspects:1) Since the histogram is independent of position of a pixel,the algorithm is resistant to geometric deformations; 2) the hash is extracted from the spatial Gaussian-filtering low-frequency component for those common video processing operations such as noise corruption,low-pass filtering,lossy compression,etc.; 3) a temporal Gaussian-filtering operation is designed so that the hash is resistant to temporal desynchronization operations,such as frame rate change and dropping.As a result,the hash function is robust to common geometric distortions and video processing operations.Experimental results show that the proposed hashing strategy can provide satisfactory robustness and uniqueness. 相似文献
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Rezaie Farshad Helfroush Mohammad Sadegh Danyali Habibollah 《Multimedia Tools and Applications》2018,77(2):2529-2541
Multimedia Tools and Applications - Objective quality assessment metrics that are consistent with human judgments of image quality, play an important role in many image processing applications.... 相似文献
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Human detection is a central problem in development of any surveillance application. In this study, we present a simple and efficient, multi-resolution gray scale invariant approach for multiple human detection. The multiresolution is important for objects of different size and gray scale invariance is important due to uneven illumination and within-class variability. The proposed method is based on integration of central moments upon multi-resolution gray scale invariant local binary patterns operator. Since, the local binary patterns operator is invariant against different resolutions of space scale and monotonic change in gray scale, therefore the proposed method is robust in terms of variations in space scale as well as gray scale. Another advantage is high computational accuracy of the method due to use of moment operator which enhances the efficiency of the proposed method. Moreover, the proposed method is simple, as these operations can be performed within a few steps in a small neighborhood and a lookup table. The proposed method is tested on multiple human images and experimentally found appropriate for multiple human detection. The proposed method has been evaluated over two datasets, one is our own created dataset and the other is standard INRIA human detection dataset. Experimental results obtained from the proposed method demonstrate that better discrimination can be achieved for human and non-human objects in real scenes. 相似文献