DocumentCode :
2940417
Title :
Elliptic Object Features Extraction and Measurement in Image Data Mining
Author :
You, Fu Cheng ; Zhang, Yong Bin
Author_Institution :
Inf. & Mech. Eng. Sch., Beijing Inst. of Graphic Commun., Beijing, China
Volume :
1
fYear :
2009
fDate :
11-12 April 2009
Firstpage :
461
Lastpage :
464
Abstract :
In image data mining, especially in mining of high dimensional association rules, extracting features of shape, color and texture is not enough for these tasks. All kinds of the features of object are often extracted. These object features of image include visual features, statistical features, and dimensional features and so on. This paper proposes an integrated method for object features extraction to meet the expression demand of high dimensional association rules. At last, the validity has been proven by an instance.
Keywords :
data mining; feature extraction; image processing; statistical analysis; association rule; dimensional features; elliptic object feature extraction; image data mining; parameter measurement; statistical features; visual features; Association rules; Automation; Data mining; Feature extraction; Graphics; Mechanical engineering; Mechanical variables measurement; Mechatronics; Pixel; Shape measurement; image data mining; object features extraction; parameter measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation, 2009. ICMTMA '09. International Conference on
Conference_Location :
Zhangjiajie, Hunan
Print_ISBN :
978-0-7695-3583-8
Type :
conf
DOI :
10.1109/ICMTMA.2009.31
Filename :
5203011
Link To Document :
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