Title :
A new method for edge detection based on support vector classification
Author :
Lei, Jing ; Shen, Xue-Qin
Author_Institution :
Hebei Univ. of Technol., Tianjin, China
Abstract :
An edge detection method based on a support vector machine is introduced. We use support vector classification (SVC) to detect image edges. With support vector classification, we can observe that: (1) it is very convenient for gray level images whose background and foreground lightness have large differences; (2) we can compress the images through the so-called support vector.
Keywords :
data compression; edge detection; image classification; image coding; learning automata; edge detection; gray level image; image compression; support vector classification; support vector machine; Face detection; Image edge detection; Lagrangian functions; Machine learning; Pixel; Static VAr compensators; Support vector machine classification; Support vector machines; Training data; Virtual colonoscopy;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1175339
