A new feature for image retrieval using a'trous wavelet transform and textons

In this paper, a combination of a`trous wavelet transform (AWT) and Julesz's texton theory is used for feature extraction and retrieval of the images from natural image database. AWT is used to decompose the image and different texton elements are used to detect the spatial co-relation among the transform pixels in horizontal, vertical, diagonal and minor diagonal directions. Further, this information is combined with texture oriented image for generation of image feature vector. The proposed method is tested on Corel 1000 and 2500 image database and the retrieval results have demonstrated significant improvement in average precision, average weighted precision, average recall rate, average rank, standard deviation of rank, standard deviation of precision as well as feature extraction and retrieval time compared to optimal quantised wavelet correlogram (OQWC) and Gabor wavelet correlogram (GWC).

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