Abstract
Canny Edge Detector is the most widely used operator for edge detection. The problem with Canny is that it outputs a binary edge map, where an edge pixel (edgel) is marked (e.g., its value in the edge map is 255) and a non-edge pixel is unmarked (e.g., its value in the edge map is 0). A typical binary edge map is of low quality, consisting of gaps, notch-like structures, ragged and multi-pixel wide edgels. To clean up Canny's binary edge maps, fill up one pixel-wide gaps between the edgels, and to return the map as a set of edge segments, each of which is a one-pixel wide, contiguous chain of pixels, we employ the Smart Routing (SR) algorithm from our recently proposed Edge Segment Detection Algorithm, the Edge Drawing (ED). The proposed algorithm, called Canny Smart Routing (CannySR), runs Canny to obtain a binary edge map, and uses the Canny edgels as anchors for SR to convert them to edge segments. The produced edge segments can then be used in many applications such as line, arc, circle, ellipse, corner detection and other similar higher level object detection applications. We qualitatively evaluate the effectiveness of the proposed algorithm on some sample images and conclude that CannySR visibly improves the modal quality of Canny's binary edge maps although ED seems to produce the best results.
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