Under high magnification of the micro-vision systems, the original metal texture appears in the form of bright spots with different shapes and different sizes and mixes with the real flaws such as maculae, pockmarks, and corrosions. The background of the image is complex while the image brightness is non-uniform due to the spherical reflection. It is difficult to extract the flaws accurately by means of traditional segmentation methods. In this paper, a new method for detecting flaws automatically is presented, in which the flaws are located approximately at first by removing the uniform background and the bright spots of metal surface texture, then detected accurately using the method of double-window. The experimental results show that this method is effective to detect various flaws on the surface of metal sphere.
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