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Image Retrieval Based on Structured Local Binary Kirsch Pattern

机译:基于结构化局部二值Kirsch模式的图像检索

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摘要

This Letter presents a new feature named structured local binary Kirsch pattern (SLBKP) for image retrieval. Each input color image is decomposed into Y, Cb and Cr components. For each component image, eight 3×3 Kirsch direction templates are first performed pixel by pixel, and thus each pixel is characterized by an 8-dimenional edge-strength vector. Then a binary operation is performed on each edge-strength vector to obtain its integer-valued SLBKP. Finally, three SLBKP histograms are concatenated together as the final feature of each input colour image. Experimental results show that, compared with the existing structured local binary Haar pattern (SLBHP)-based feature, the proposed feature can greatly improve retrieval performance.
机译:这封信提出了一项新功能,称为结构化本地二进制Kirsch模式(SLBKP),用于图像检索。每个输入彩色图像被分解为Y,Cb和Cr分量。对于每个分量图像,首先逐个像素地执行八个3×3 Kirsch方向模板,因此每个像素都具有8维边缘强度矢量。然后,对每个边缘强度矢量执行二进制运算以获得其整数值SLBKP。最后,将三个SLBKP直方图连接在一起,作为每个输入彩色图像的最终特征。实验结果表明,与现有的基于结构化局部二进制Haar模式(SLBHP)的特征相比,该特征可以大大提高检索性能。

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