Abstract
This paper studies principle of the traditional Canny edge detection algorithm and the existing problems. Some solutions toward the problems are also proposed. The improvement methods consisted of two parts. On the one hand, as Canny edge algorithm itself does not have strong noise immunity while ensuring edge positioning accuracy, an adaptive median filter denoising program based on the Canny Gaussian filter is proposed to enhance the Canny algorithm filter performance. On the other hand, given the Canny algorithm high and low threshold parameter is not determined by the feature information of the image edge, but rather set manually which does not have the adaptive ability, this paper proposes an adaptive threshold setting scheme for high and low thresholds to improve the adaptive ability of Canny algorithm to different images.
Highlights
The image edge information is important both for human being and machine vision
Advanced Engineering Forum Vols. 6-7. As these problems affect the application of Canny algorithm in a large extent, this article addresses some ideas to improve the Canny algorithm. With these ideas, following objectives can be realized: 1 to achieve a balance between edge positioning accuracy and noise suppression effect. 2 to achieve the self-adaptive determination of high and low thresholds of edge detection to further improve the effect of the edge detection of Canny algorithm
After studed various research toward image smoothing algorithm, this paper proposes an adaptive median filter based on the traditional Canny Gaussian filter
Summary
The image edge information is important both for human being and machine vision. There are various geometric forms of gray-scale mutations, and the most common one is the laplace domain edge. Among all the existing edge detection algorithms, Canny algorithm is a good one and is widely used. (2) High positioning precision, refers to accurately locate the edge points at the pixel which has the biggest gray change. This paper analyzes the advantages and disadvantages of traditional Canny algorithm, and proposes the improvement solutions toward existing problems of this algorithm.
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