DocumentCode :
3448240
Title :
Image mining for robot vision based on concept analysis
Author :
Xiao, Qizhi ; Qin, Kun ; Guan, Zequn ; Wu, Tao
Author_Institution :
Sch. of Remote Sensing Inf. Eng., Wuhan Univ. Wuhan, Wuhan
fYear :
2007
fDate :
15-18 Dec. 2007
Firstpage :
207
Lastpage :
212
Abstract :
- In the process of image mining for robot vision, concept analysis is an important technique. The paper proposes a novel framework of image mining for robot vision based on concept lattice theory and cloud model theory. Concept lattice reflects the process of human´s concept formation with mathematical formal language. Cloud model is a transformation model between qualitative concepts and quantitative numerical values. Image mining for robot vision is considered as a process of concept extraction from different granularities (image pixels, image pixel groups, image features, image objects, image files and image databases). The methods of image mining from image features(texture features, color features, shape features, spatial relationship features) are introduced in the paper, which include the following basic steps: firstly pre-process images, secondly use cloud model to extract concepts, lastly use concept lattice to extract a series of image knowledge(association rules, clustering rules and classification rules). At last, a software prototype is designed and developed, and some experiments confirm the validity of the proposed framework.
Keywords :
data mining; feature extraction; image colour analysis; image texture; robot vision; cloud model theory; color feature; concept lattice theory; image mining; robot vision; shape feature; spatial relationship feature; texture feature; Clouds; Formal languages; Image analysis; Image databases; Lattices; Pixel; Robot vision systems; Shape; Software design; Software prototyping; cloud model; concept analysis; concept lattice; image mining; robot vision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics, 2007. ROBIO 2007. IEEE International Conference on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-1761-2
Electronic_ISBN :
978-1-4244-1758-2
Type :
conf
DOI :
10.1109/ROBIO.2007.4522161
Filename :
4522161
Link To Document :
بازگشت