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Title:
Extracting Dominant Textures in Real Time With Multi-Scale Hue-Saturation-Intensity Histograms
Author: Wang, Wencheng ; Hua, Miao
Keyword: Clustering methods ; feature extraction ; image texture ; real time systems
Source: IEEE TRANSACTIONS ON IMAGE PROCESSING
Issued Date: 2013
Volume: 22, Issue:11, Pages:4237-4248
Indexed Type: SCI
Department: [Wang, Wencheng; Hua, Miao] Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100190, Peoples R China. [Hua, Miao] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.
Abstract: It is very important to extract high quality texture features from images. This is, however, often laborious, because the randomness in the color distribution patterns for texture elements makes texture measurement very difficult, despite these elements having a very similar visual appearance. In this paper, we propose the use of multi-scale color histograms to measure the effect of color distribution patterns efficiently and without having to compute the actual patterns, which saves considerable effort. Meanwhile, the hue-saturation-intensity color model is mainly adopted to take the advantage of human visual experiences in texture recognition. We discuss and validate the effectiveness and efficiency of our method by applying to various benchmarks. The results show that we can extract quality dominant textures automatically in real time, and faster by several orders of magnitude than existing methods.
English Abstract: It is very important to extract high quality texture features from images. This is, however, often laborious, because the randomness in the color distribution patterns for texture elements makes texture measurement very difficult, despite these elements having a very similar visual appearance. In this paper, we propose the use of multi-scale color histograms to measure the effect of color distribution patterns efficiently and without having to compute the actual patterns, which saves considerable effort. Meanwhile, the hue-saturation-intensity color model is mainly adopted to take the advantage of human visual experiences in texture recognition. We discuss and validate the effectiveness and efficiency of our method by applying to various benchmarks. The results show that we can extract quality dominant textures automatically in real time, and faster by several orders of magnitude than existing methods.
Language: 英语
WOS ID: WOS:000324597800007
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/16908
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Wang, Wencheng,Hua, Miao. Extracting Dominant Textures in Real Time With Multi-Scale Hue-Saturation-Intensity Histograms[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2013-01-01,22(11):4237-4248.
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