一种基于奇异值分解的彩色图像检索方法

Junali Jasmine Jena, Manisha Patro, G. Girish
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引用次数: 2

摘要

为了提高模式匹配的准确性,可以对适当分解的图像应用局部模式匹配算法。本文将奇异值分解(SVD)技术和局部二值模式(LBP)算法应用于RGB色彩空间中的图像。对RGB的各个分量分别获取特征向量,然后进行合并得到最终的特征向量。在这些特征向量上进行的CBIR得到了更好的结果,LBP-S-RGB技术的精密度、召回率和f得分分别为56.08、84.13和67.3,最佳桶大小为256。
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A SVD Based Pattern Matching Approach for Color Image Retrieval
To make the pattern matching more accurate, local pattern matching algorithms could be applied upon suitably decomposed images. In this paper, SVD (Singular Value Decomposition) technique followed by LBP (Local Binary Pattern) algorithm has been applied to the images in RGB color space. Feature vectors are obtained for individual component of RGB and then merged to get the final feature vector. CBIR performed upon these feature vectors yielded better results and values of precision, recall and f-score was found to be 56.08, 84.13 and 67.3 respectively for the technique LBP-S-RGB with an optimal bin-size of 256.
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