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首页> 外文期刊>International journal of computational vision and robotics >Image retrieval using improved texton co-occurrence matrix
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Image retrieval using improved texton co-occurrence matrix

机译:使用改进的texton共现矩阵进行图像检索

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摘要

This paper proposed a new technique for content-based image retrieval (CBIR) using a combination of a' trous wavelet transform (AWT) and Julesz's texton elements. AWT is used to decomposse the image into different scales and different texton elements are used to detect the spatial co-relation among the transform coefficients in horizontal, vertical, diagonal and minor diagonal directions which results into texton image. Further co-occurance operations are performed on texton image in horizontal and zigzag direction. Texton co-occurance matrix gives second order statistics related to texton image.The proposed method is tested on natural database (Corel 1000 and Corel 2500) and texture database (Brodatz and USC texture database) and the retrieval results have demonstrated significant improvement in average precision, average recall rate, as well as feature extraction and retrieval time compared to optimal quantised wavelet correlogram (OQWC) and Gabor wavelet correlogram (GWC).
机译:本文提出了一种新的基于内容的图像检索(CBIR)技术,该技术结合了trous小波变换(AWT)和Julesz的texton元素。 AWT用于将图像分解为不同的比例,并且不同的texton元素用于检测水平,垂直,对角线和次对角线方向上变换系数之间的空间相关性,从而形成texton图像。在水平和Z字形方向上的texton图像上执行其他共存操作。 Texton共生矩阵给出与Texton图像有关的二阶统计量。该方法在自然数据库(Corel 1000和Corel 2500)和纹理数据库(Brodatz和USC纹理数据库)上进行了测试,检索结果表明平均精度有显着提高,平均召回率,以及与最佳量化小波相关图(OQWC)和Gabor小波相关图(GWC)相比的特征提取和检索时间。

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