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Open AccessArticle

Effective Image Retrieval Using Texture Elements and Color Fuzzy Correlogram

College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
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Academic Editor: Laurent Heutte
Information 2017, 8(1), 27; https://doi.org/10.3390/info8010027
Received: 30 November 2016 / Revised: 20 February 2017 / Accepted: 23 February 2017 / Published: 25 February 2017
(This article belongs to the Section Information Processes)
Image low-level information, such as color, texture, and shape, were generally dealt with separately and combined together gruffly. Their image-describing effect in image retrieval was weakened. This paper determines and extracts one group of texture elements from images to mainly express the image texture information and, during this procedure, the quantized HSV color information is added to develop the feature, Color Layer-Based Texture Elements Histogram (CLBTEH). Furthermore, Color Fuzzy Correlogram (CFC) is put forward and employed for further extraction of color features. The performance of the proposed approach is evaluated on different image databases, including Corel-1k, Corel-10k, and USPTex1.0, and it was found that the experimental results of the proposed approach are encouraging in comparison with similar algorithms. View Full-Text
Keywords: feature extraction; image retrieval; color layer based texture elements histogram; color fuzzy correlogram feature extraction; image retrieval; color layer based texture elements histogram; color fuzzy correlogram
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MDPI and ACS Style

Yang, F.-p.; Hao, M.-l. Effective Image Retrieval Using Texture Elements and Color Fuzzy Correlogram. Information 2017, 8, 27.

AMA Style

Yang F-p, Hao M-l. Effective Image Retrieval Using Texture Elements and Color Fuzzy Correlogram. Information. 2017; 8(1):27.

Chicago/Turabian Style

Yang, Fu-ping; Hao, Mei-li. 2017. "Effective Image Retrieval Using Texture Elements and Color Fuzzy Correlogram" Information 8, no. 1: 27.

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