Authors: Anil Balaji Gonde, R.P. Maheshwari, R. Balasubramanian
Addresses: Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee – 247667, Uttarakhand, India. ' Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee – 247667, Uttarakhand, India. ' Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee – 247667, Uttarakhand, India
Abstract: 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).
Keywords: a`trous wavelet transform; AWT; textons; content-based image retrieval; CBIR; wavelet correlograms; GWC; texton theory; feature extraction; image databases; images.
International Journal of Computational Vision and Robotics, 2010 Vol.1 No.3, pp.261 - 278
Published online: 15 Jan 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article