Robust Canny Edge Detection Method Based On Multidirectional Fractional Differential

Edge detection is a very important technology in the field of image processing,which is widely used in aerospace,industrial monitoring,biomedical and other fields.The results of edge detection will directly affect other image processing results,so how to improve the accuracy of edge detection has become one of the important research issues in the field of image processing.Traditional edge detection algorithms mainly include methods based on first-order differential and second-order differential operators.Although these methods are simple and easy to implement,they are sensitive to noise in the process of edge detection,and there are false detection,missing detection and bilateral phenomena in the detection results.Therefore,this paper proposes a robust Canny edge detection method based on multidirectional fractional order differential to solve the problems of false detection,missing detection and bilateral in traditional edge detection methods.The main work and research results are as follows:1?Considering the false detection,missed detection and bilateral phenomenon in the detection results of traditional edge detection algorithm,this paper improves the edge detection template of traditional Canny algorithm,and deduces the edge detection template based on eight direction fractional order differential operator.Based on the template,a canny edge detection algorithm based on eight direction fractional order differential operator is proposed,and the effectiveness of the method is verified by simulation.2?In order to solve the problem of edge breaking in Canny edge detection method based on eight direction fractional differential operator,a gradient vector flow is proposed,GVF)snake model of edge repair and reconstruction method,the method to detect the edge of the broken edge as the object,according to the local edge structure,repair the broken edge,improve the robustness of Canny edge detection method proposed in this paper.3?In order to verify the effectiveness of robust Canny edge detection method based on multidirectional fractional order differential to solve practical engineering problems,this method is applied to edge detection of workpiece and silicon single crystal diameter detection image in high temperature red hot state.Experimental results show that this method can effectively detect the edge of workpiece and silicon single crystal image,and reduce the error detection rate of edge detection method and missing rate.To sum up,an edge detection template of eight direction fractional order differential operator is proposed to improve the accuracy of image edge detection;secondly,combined with GVF Snake model algorithm,a robust Canny edge detection method based on multidirectional fractional order differentiation is proposed,in which multidirectional is the eight directions mentioned in this paper.Finally,the effectiveness of the algorithm proposed in this paper is verified by edge detection of the workpiece image and the silicon single crystal image in the high-temperature red hot state.