Contourlet-1.3 Texture Retrieval with Energy, Standard Deviation and Kurtosis

• Published in: Applied Mechanics and Materials Vol. 446-447; no. Advanced Research in Material Science and Mechanical Engineering; pp. 1347 - 1352
• Main Authors: Guo, Zhen, Chen, Xin Wu
• Format: Journal Article
• Language: English
• Published: Zurich Trans Tech Publications Ltd 01.11.2013
• Subjects: Kurtosis; Retrieval; Shape; Standard deviation; Surface layer; Texture; Transforms; Texture Image; Retrieval Rate; Retrieval System; Content Based Image Retrieval; Contourlet-1.3 Transform
• ISBN: 9783037859087; 3037859083
• ISSN: 1660-9336; 1662-7482; 1662-7482
• DOI: 10.4028/www.scientific.net/AMM.446-447.1347

Contourlet-1.3 transform has better performance in directional information representation than the original contourlet transform due to less artifacts and local frequency characteristics, and has been studied by us in retrieval systems and has been shown it is superior to contourlet ones at retrieval rate. In order to improve the retrieval rate further, a novel contourlet-1.3 transform based texture image retrieval system was proposed in this paper. In the system, sub-bands energy, standard deviation and kurtosis in contourlet domain were cascaded to form feature vectors, and the similarity measure function was Canberra distance. Experimental results show that this contourlet-1.3 transform based image retrieval system has higher retrieval rates about 7% to that of the contourlet transform with absolute mean sub-bands energy and standard deviations features under same system structure.