A Sensation Model for Color Images' Cognition

被引:0
|
作者
Li, ZhongSheng [1 ]
Huang, TongCheng [1 ]
Niu, Li [1 ]
Cai, ZeSu [2 ]
机构
[1] Shaoyang Univ, Dept Informat Engn, Shaoyang, Peoples R China
[2] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin, Peoples R China
来源
SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4 | 2013年 / 303-306卷
基金
中国国家自然科学基金;
关键词
Single Concept Clustering(SCC); semantic partitioning; data processing task; Rough Set;
D O I
10.4028/www.scientific.net/AMM.303-306.1489
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
It's a new idea to make computers be able to obtain "sensations" from a color image through some unsupervised ways. To let the idea come into true, a granule-based model, based on granular computing(GrC) which is a new way to simulate human thinking to help solve complicated problems in the field of computational intelligence, is proposed for color image processing. First, this paper deems data a hypercube, defines two new concepts, attribute granules(AtG) and connected granules(CoG), and presents the definitions of the granule-based model. Then, in order to fulfill the granule-based model, this paper designs a single attribute analyser(SAA), defines some theorems and lemmas related to decomposition, and describes the processing of extracting all attibute granules. Experimental results on over 300 color images show that the proposed analyser is accurate, robust, high-speed, and able to provide computers with "sensations".
引用
收藏
页码:1489 / +
页数:2
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