Title :
The Image Retrieval Based on Scale and Rotation-Invariant Texture Features of Gabor Wavelet Transform
Author :
Chen Gang ; Chen Ning ; Lin Xia
Author_Institution :
Coll. of Math. & Comput. Sci., Jianghan Univ. Wuhan, Wuhan, China
Abstract :
A scale and rotation invariant texture features extraction method is proposed and then the extracted texture features are used for image retrieval. In this method, firstly, features vector of each angle after the Gabor wavelet transform is multiplied by a Gaussian window, and then a circular shift is applied on it to shift the maximum value to be the first element, which makes the scale invariance achieved, then a circular shift is applied on the features vector to shift the maximum value to be the first element of each scale which makes the rotation invariant achieved. After that, texture features are extracted form the Gabor wavelet transform after scale and rotation invariant. Finally, the extracted texture features is used for images retrieval, the similarity is measured by Canberra distance and the retrieval effectiveness is assessed by P-R(Precision-Recall) carve and MAP(Mean Average Precision). The experimental results show that this method can accurately extract scale and rotation invariant texture features.
Keywords :
Gabor filters; Gaussian processes; content-based retrieval; feature extraction; image retrieval; image texture; wavelet transforms; CBIR; Canberra distance; Gabor wavelet transform; Gaussian window; MAP; P-R carve; circular shift; content-based image retrieval; feature vector; mean average precision; precision-recall carve; rotation-invariant texture feature extraction method; scale invariant texture feature extraction method; similarity measurement; Feature extraction; Gabor filters; Image retrieval; Manganese; Vectors; Wavelet transforms; Gabor wavelet transform; Gaussian window; rotation invariant; scale invariant; texture retrieval;
Conference_Titel :
Software Engineering (WCSE), 2013 Fourth World Congress on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4799-2882-8
DOI :
10.1109/WCSE.2013.64