Content-based Image Retrieval Using Texture Features Extracted from Local Energy and Local Correlation of Gabor Transformed Images
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초록
In this paper, a texture feature extraction method using local energy and local correlation of Gabortransformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known tobe similar to the response of the human visual system. The outputs of the Gabor transformation are robustto variants of object size and illumination. Due to such advantages, it has been actively studied in variousfields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superioraspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformedimages and then applied to an image retrieval system. Some experiments are conducted to compare theperformance of the proposed method with those of the conventional Gabor method and the popularrotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. TheMahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to theconventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66%higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB,respectively, than the popular RULBP method.
Abstract
In this paper, a texture feature extraction method using local energy and local correlation of Gabortransformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known tobe similar to the response of the human visual system. The outputs of the Gabor transformation are robustto variants of object size and illumination. Due to such advantages, it has been actively studied in variousfields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superioraspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformedimages and then applied to an image retrieval system. Some experiments are conducted to compare theperformance of the proposed method with those of the conventional Gabor method and the popularrotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. TheMahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to theconventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66%higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB,respectively, than the popular RULBP method.
참고문헌 (22)
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