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Local co-occurrence pattern for color and texture image retrieval

机译:用于颜色和纹理图像检索的局部共现模式

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Local patterns have two problems: 1) the traditional local patterns methods only consider the frequency of each pattern, and does not consider the co-occurrence information between adjacent pixels pairs in the image; 2)the traditional methods limit on the gray texture analysis, ignoring the importance of color information. To address above problems, a novel method is proposed for color image retrieval using CLGBCOP (Color Local Gabor binary Co-occurrence Pattern). In this work, global color information is extracted by using color quantization, and the combination of LBCOP (Local binary Co-occurrence Pattern) and Gabor Transform is applied to extract texture information. LBCOP encodes the co-occurrence of local binary edges between center pixel and its neighbors along different directions. Extensive experiments are conducted on Corel-1000, Corel-5000 and Corel-10000 databases to verify the feasibility of the proposed method.
机译:局部图案有两个问题:1)传统的局部图案方法只考虑每个图案的频率,而不考虑图像中相邻像素对之间的共现信息; 2)传统方法限制了灰色纹理分析,而忽略了颜色信息的重要性。为了解决上述问题,提出了一种使用CLGBCOP(颜色局部Gabor二进制共现模式)进行彩色图像检索的新方法。在这项工作中,通过使用颜色量化来提取全局颜色信息,并应用LBCOP(局部二进制共现模式)和Gabor变换的组合来提取纹理信息。 LBCOP编码中心像素及其相邻像素之间沿不同方向共存的本地二进制边缘。在Corel-1000,Corel-5000和Corel-10000数据库上进行了广泛的实验,以验证该方法的可行性。

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