Abstract
Because of the vigorous growth in the electronic industry, the quantity and variety of products has risen enormously. In order to pursue profits, a strategy of cost-reduction is necessary. Automatic optical inspection (AOI) has been widely used in the inspection process of printed circuit board assembles (PCBAs); however, unrecognized deficiencies still occur. In order to increase precision in recognizing a PCBA's deficiencies by using current inspection techniques, a huge quantity of samples used in off-line training is obligatory. Unfortunately, it is not suitable for an industry which produces a variety of products with a smaller quantity. Traditional AOI methods have been investigated and substantially tested in this paper. Results reveal that many image errors which haven't been identified may raise maintenance cost of PCBAs. To overcome the above drawbacks, a new and efficient algorithm, an image division method (IDM), is proposed. Consequently, the experimental results using the IDM reveal that recognition efficiency can be improved.
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