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