An Improved Neural Networks Based Edge Detection Method

| Existing edge detection methods provide unsatisfactory results when contrast changes largely within an image due to non-uniform illumination. Koch et al. developed an energy function based upon Hop eld neural network, whose coe cients were xed by trial and error and remains constant for the entire image, irrespective of the di erences in intensity level. This paper presents an improved edge detection method for images where contrast is not uniform. we propose that the energy function parameters for an image with inconsistent illumination should not remain xed and propose an schedule to change these parameters. The results, compared with those of existing one's, suggest a better strategy for edge detection depending upon both the dynamic range of the original image pixel values as well as their contrast.