Title :
Color Image Edge Detection using Dempster-Shafer Theory
Author :
Chunjiang, Zhao ; Yong, Deng
Author_Institution :
Dept. of Electron. Inf. & Electr. Eng., Hefei Univ., Hefei, China
Abstract :
New color image edge detection is proposed in this paper. Dempster-Shafer theory, also known as the theory of belief function, is applied in the color image edge detection. The reason is that by selecting the mass function, Dempster-Shafer theory can distinguish the edge pixels from the uncertain edge pixels correctly. Firstly, the color image is transformed into R, G and B components; then in these three components, the edge gradient magnitude images are obtained by the Sobel operator respectively; thirdly, the mass functions are selected and the orthogonal sum is calculated; finally, the mass function of the edge probability is regarded as the edge image. From the experiment, the result could be accepted.
Keywords :
edge detection; image colour analysis; inference mechanisms; probability; uncertainty handling; Dempster-Shafer theory; RGB components; Sobel operator; belief function theory; color image edge detection; edge gradient magnitude images; edge pixels; edge probability; mass function; Artificial intelligence; Cameras; Computational intelligence; Distributed computing; Image color analysis; Image edge detection; Image processing; Probability; Uncertainty; Dempster-Shafer theory; color image; edge detection;
Conference_Titel :
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3835-8
Electronic_ISBN :
978-0-7695-3816-7
DOI :
10.1109/AICI.2009.34