Detection of surface cutting defect on magnet using Fourier image reconstruction

Abstract

A magnet is an important component of a speaker, as it makes the coil move back forth, and it is commonly used in mobile information terminals. Defects may appear on the surface of the magnet while cutting it into smaller slices, and hence, automatic detection of surface cutting defect detection becomes an important task for magnet production. In this work, an image-based detection system for magnet surface defect was constructed, a Fourier image reconstruction based on the magnet surface image processing method was proposed. The Fourier transform was used to get the spectrum image of the magnet image, and the defect was shown as a bright line in it. The Hough transform was used to detect the angle of the bright line, and this line was removed to eliminate the defect from the original gray image; then the inverse Fourier transform was applied to get the background gray image. The defect region was obtained by evaluating the gray-level differences between the original image and the background gray image. Further, the effects of several parameters in this method were studied and the optimized values were obtained. Experiment results show that the proposed method can detect surface cutting defects in a magnet automatically and efficiently.