In this research, a method to detect minute flaws on metal parts is proposed to remove the defective parts before assembling in a factory. The input gray-scale images of metal parts are used directly to recognize the flaw without any image conversion to shorten the recognition time. The recognition problem to find defects and detect its position on the metal parts is converted here to another problem to search for the maximum peak and the variables giving the peak. Then the recognition problem can be treated as optimization problem, and this conversion allow us to utilize the high performances of GAin the optimization. The effectiveness of proposed method is studied on standing points of the recognition speed and the quantitative recognition ability.
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