Research on Image Edge Detection Method Based on Multi-sensor Data Fusion

In the process of defect detection of metal components, defect edge detection is very important, and the accuracy of abnormal edge directly affects the subsequent inversion evaluation. Aiming at the fuzzy problem of defect edges in metal component detection images, this paper proposes an image edge detection algorithm based on multi-sensor data fusion. The algorithm uses the detection results of three types of sensors: ultrasonic, eddy current and magnetic flux leakage to perform feature extraction, and wavelet transform is used for image fusion. Modular maximum edge detection is performed on the fused data, and the experimental results prove the effectiveness of the proposed algorithm.