Currently, conventional methods for detecting internal defects in bearings are mainly based on enhancing the laser image of bearings so as to amplify the features of defects and realize defect detection by means of connectivity domain marking, etc. The detection accuracy is poor due to the low dimensionality of the filtering process of the image. In this regard, a laser detection method for internal bearing defects based on edge extraction and curve fitting is proposed. Firstly, the filter size is selected in combination with the filtering requirements, and according to the complexity of the image, one-dimensional as well as two-dimensional filtering is carried out respectively. Then the coordinates of the pixel points on the middle line of the binary distribution map of the derivative sign are extracted to mark the center line of the original diffraction stripe image. Finally, the defect edge line is extracted by combining the Sobel operator, and the edge line fitting process is realized by calculating the square and the mean difference of the defect edge, so that the background image and the defect contour image are separated from the original image to realize the defect detection. In the experiments, the detection accuracy of the proposed method is tested. The final test results show that when the proposed method is used to detect bearing defects, the peak signal-to-noise ratio and image structure similarity of the detected images is high, and the detection effect is more ideal.