Content Based Image Retrieval using Discrete Wavelet Transform and Edge Histogram Descriptor

S. Agarwal, A. K. Verma, Pardeep Singh
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引用次数: 75

Abstract

This paper describes an efficient algorithm for Content Based Image Retrieval (CBIR) based on Discrete Wavelet Transform (DWT) and Edge Histogram Descriptor (EHD) feature of MPEG-7. The proposed algorithm is explained for image retrieval based on shape and texture features only not on the basis of color information. Here input image is first decomposed into wavelet coefficients. These wavelet coefficients give mainly horizontal, vertical and diagonal features in the image. After wavelet transform, Edge Histogram Descriptor is then used on selected wavelet coefficients to gather the information of dominant edge orientations. The combination of DWT and EHD techniques increases the performance of image retrieval system for shape and texture based search. The performance of various wavelets is also compared to find the suitability of particular wavelet function for image retrieval. The proposed algorithm is trained and tested for Wang image database. The results of retrieval are expressed in terms of Precision and Recall and compared with various other proposed schemes to show the superiority of our scheme.
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基于离散小波变换和边缘直方图描述符的图像检索
提出了一种基于离散小波变换(DWT)和MPEG-7边缘直方图描述子(EHD)特征的基于内容的图像检索(CBIR)算法。说明了该算法仅基于形状和纹理特征而不基于颜色信息进行图像检索。输入图像首先被分解成小波系数。这些小波系数主要给出图像的水平、垂直和对角特征。小波变换后,对选取的小波系数使用边缘直方图描述子来获取优势边缘方向信息。DWT和EHD技术的结合提高了基于形状和纹理搜索的图像检索系统的性能。比较了不同小波函数的性能,确定了特定小波函数在图像检索中的适用性。在Wang图像数据库中对该算法进行了训练和测试。检索结果以查准率(Precision)和查全率(Recall)表示,并与其他方案进行比较,以显示我们方案的优越性。
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