An Adaptive Threshold Canny Edge Detection Method for Applications with Simple Background

Abstract

Edge detection is an important image processing problem with many practical applications in different fields. While many methods have been proposed, further improvements still need to be made for specific applications. This paper focuses on the application of Canny edge in the image with a simple background, proposed an adaptive threshold Canny edge detection method. Considering the distribution of the object and the solid-color background, a pixels intensity statistic is operated for the corresponding gray image. In this way, the double thresholds are determined by analyzing the statistical result. Furthermore, to verify the effectiveness of the proposed method, experiments are done on images that are taken with different conditions. The result shows that Canny edge can be well detected by utilizing the two adaptive threshold values and have strong robustness to different conditions. Particularly in the applications, such as object detection and image segmentation, the adaptive threshold Canny edge detection method plays a meaningful role.