Edge detection by neural network with line process
Md. Shoaib Bhuiyan, Masa-aki Sato, Hideyuki Fujimoto, Akira Iwata · 2005
Though edge detection is an indispensable part in image processing, no definite method still exists. Existing methods can not detect edge precisely when contrast changes largely within the object due to non-uniform illumination. Geman and Geman applied a line process to express the discontinuity in gray level of images. Variation of contrast in an image still remains a problem. Koch et al. developed an energy equation whose coefficients remained constant. This paper presents an edge detection method for images where contrast is not uniform. It shows an way of changes in coefficients of the line process energy equation. Besides, use of neural network helps to reduce noise, thereby making human intervention unnecessary in the detection of edge.