Sub-Block based Color Moments, Wavelet and Edge Histogram for Image Retrieval

Authors Name: Naveena AK1, N K Narayanan2 


This paper proposes a novel image retrieval algorithm using local color feature of image sub-block and global texture and shape features. Image sub-blocks are identified by partitioning the image into blocks. Color Texture and shape are the low level image descriptor in Content Based Image Retrieval. These low level image descriptors are used for image representation and retrieval in CBIR. In this paper a Content Base Image Retrieval (CBIR) System using the image features extracted by color moments, wavelet and edge histogram is presented. Combining the color, texture and shape feature leads to a more accurate result for image retrieval. Moreover the color moments are taken by partitioning the images into blocks hence it also gives spatial color information. Here SVM classifier is used to classify the images into different class and the similarity measure is taken only with the images in the same class.

Keywords: sub-block CBIR; color moment; wavelet; edge histogram; SVM

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