Discrimination of Thin Stains and Foreign Particles on Electronic Parts’ Surface

Abstract

In this paper, an image processing method to detect thin stains and particles on a surface image is described. The method aims not only to detect the objects but also to distinguish relatively large stains and relatively small particles. In conventional studies, a Fourier transform image processing method to detect the objects is applied. A frequency-transmitting mask applied on a Fourier transformed plane has been used. It is shown that a specific size ring mask enables the detection of specific sized objects. However, when the method is applied to detect stains, it miss-detects elongated particles and the dense particles beside stains. This is because the mask for detecting stains also transmit those particles' frequency components as those particles images contain a wide range of frequency components. The proposed method, first detects the particle image. Then, the original image is subtracted from the processed image to get a particle suppressed image. By applying a stain detecting mask to this image, it was possible to detect stains without miss-detection.