Content-Based Image Retrieval Using Combined Color and Texture Features Extracted by Multi-resolution Multi-direction Filtering

Hee-Hyung Bu, Nam-Chul Kim, Chae-Joo Moon and Jong-Hwa Kim
Volume: 13, No: 3, Page: 464 ~ 475, Year: 2017
10.3745/JIPS.02.0060
Keywords: Color and Texture Feature, Content-Based Image Retrieval, HSV Color Space, Multi-resolution Multi-direction Filtering
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Abstract
In this paper, we present a new texture image retrieval method which combines color and texture features extracted from images by a set of multi-resolution multi-direction (MRMD) filters. The MRMD filter set chosen is simple and can be separable to low and high frequency information, and provides efficient multi- resolution and multi-direction analysis. The color space used is HSV color space separable to hue, saturation, and value components, which are easily analyzed as showing characteristics similar to the human visual system. This experiment is conducted by comparing precision vs. recall of retrieval and feature vector dimensions. Images for experiments include Corel DB and VisTex DB; Corel_MR DB and VisTex_MR DB, which are transformed from the aforementioned two DBs to have multi-resolution images; and Corel_MD DB and VisTex_MD DB, transformed from the two DBs to have multi-direction images. According to the experimental results, the proposed method improves upon the existing methods in aspects of precision and recall of retrieval, and also reduces feature vector dimensions.

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Cite this article
IEEE Style
Hee-Hyung Bu, Nam-Chul Kim, Chae-Joo Moon, Jong-Hwa Kim, "Content-Based Image Retrieval Using Combined Color and Texture Features Extracted by Multi-resolution Multi-direction Filtering," Journal of Information Processing Systems, vol. 13, no. 3, pp. 464~475, 2017. DOI: 10.3745/JIPS.02.0060.

ACM Style
Hee-Hyung Bu, Nam-Chul Kim, Chae-Joo Moon, Jong-Hwa Kim, "Content-Based Image Retrieval Using Combined Color and Texture Features Extracted by Multi-resolution Multi-direction Filtering," Journal of Information Processing Systems, 13, 3, (2017), 464~475. DOI: 10.3745/JIPS.02.0060.