Title :
Image segmentation through using the evidence theory based data fusion technique
Author :
Dromigny-Badin, A. ; Zhu, Y.M. ; Gimenez, G. ; Goutte, R.
Author_Institution :
INSA, CNRS, Villeurbanne, France
Abstract :
An image segmentation method is presented that is based on a pixel-level data fusion technique employing the evidence theory of Dempster-Shafer (DS). A probability mass being defined for each gray level, each couple of pixels is combined through Dempster´s combination rule and a look-up fusion table. The segmentation procedure is iterative, and the determination of probability mass is automatic. The proposed method is illustrated with the aid of both simulations and examples on physical images. The obtained results show the interest of exploiting multiple information for image segmentation
Keywords :
case-based reasoning; image segmentation; iterative methods; probability; sensor fusion; table lookup; Dempster-Shafer theory; combination rule; evidence theory; gray level; image segmentation; iterative procedure; look-up table; pixel-level data fusion; probability mass; simulations; Biomedical imaging; Histograms; Image fusion; Image segmentation; Industrial control; Magnetic resonance imaging; Optical imaging; Pixel; Ultrasonic imaging; X-rays;
Conference_Titel :
Signal Processing Proceedings, 1998. ICSP '98. 1998 Fourth International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4325-5
DOI :
10.1109/ICOSP.1998.770781