Image Recognition Algorithm and Sharpness Evaluation based on Edge Width Detection
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Yu Yuan, Yansong Deng
The edge is one of most significant features of the images, which is the basis of image analysis and recognition. When it comes to the segmentation, measurement of the object,the edge extraction and the noise resistance areof particular importance. In order to achieve the effective extraction of the image edge, this paper presents a new algorithm for the detection of image edge width. This method is based on the principle that the blurred image will lead to edge diffusion and is divided into two processing stages. The first step is aimed at calculating the maximum value of local gradients of the image, obtaining the rough edge information map of the image, and then obtaining the finer edge information map via the adaptive dual threshold selection method. In the second stage, the probability curve on the edge width of the graph is plotted, the skewness and variance are calculated, and then we can obtain the decline factor of the curve. Finally, we define the decline factor as the adjustment coefficientwhich is multiplied by the average width of the image edge and obtain the articulation value. Having analyzed the of sharpness of the image edge width which is extracted in both objective and subjective ways, the experimental results show that the edge width information extracted by this algorithm is close to the subjective evaluation of human eyes, further illustrating the feasibility of the proposed algorithm in this paper.
Edge extraction, Local gradient extreme value,Double threshold selection,Image sharpness evaluation.