DocumentCode
2636086
Title
An edge detection method for infrared image based on grey relational analysis
Author
Dongzhu Feng ; Wang, Xin ; Yuhe Liu
Author_Institution
Sch. of Electron. Eng., Xidian Univ., Xian
fYear
2008
fDate
10-12 Dec. 2008
Firstpage
1
Lastpage
5
Abstract
Edge is the boundary between an object and its background. They represent the frontier for single objects. Therefore, if the edges of imagepsilas objects can be identified with precision, all the objects can be located and their properties such as area, perimeter, shape, etc, can be calculated. It is important to identify the precise edge in infrared imaging guidance system. In the full paper we explain in detail how to use the grey relational analysis effectively to detect the edge precisely. First, we use the grey relational analysis to finish the edge detection. During the edge detection, the formula of grey relational analysis is different from the traditional edge detection which also based on the grey relational analysis. And the value of the referential sequence is also different from the tranditional one. Then we use the Zhang-Suen thinning algorithm to get the skeleton of the edge. The result show that our method can detect and obtain more precise edge pixels. In all cases, our algorithm gives improved results when compared to some more popular edge detection methods.
Keywords
edge detection; grey systems; image representation; infrared imaging; Zhang-Suen thinning algorithm; edge detection method; grey relational analysis; image representation; infrared imaging guidance system; referential sequence; Educational institutions; Image analysis; Image edge detection; Image processing; Infrared detectors; Infrared imaging; Pixel; Shape; Signal to noise ratio; Skeleton; absolute grey relational degree; edge detection; grey relational analysis; grey system theory; thinning algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Control in Aerospace and Astronautics, 2008. ISSCAA 2008. 2nd International Symposium on
Conference_Location
Shenzhen
Print_ISBN
978-1-4244-3908-9
Electronic_ISBN
978-1-4244-2386-6
Type
conf
DOI
10.1109/ISSCAA.2008.4776163
Filename
4776163
Link To Document