A New Method of Improving Performance of Canny Edge Detection

Abstract

The traditional Canny Edge Detection Method does not perform efficiently when applied to low contrast images. It creates false edges as it cannot isolate the object from the background properly while detecting edges of any image with low contrast. In response to this problem, this paper proposes a solution using which the performance of Canny Edge Detection can be improved significantly. The images subjected to edge detection is pre-processed by stretching the image histogram. Stretching the image histogram using different stretching limits results in processed images with enhanced contrast. We obtained the best result of Canny Edge Detection Method by applying the detection technique on the modified image which has the best image contrast. The edge detected images show visual proof as well as quantitative proof of the improved performance of Canny edge detection using this process.