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An automatic identification system for the OLED's black-spot detection was designed in this paper. Complete approaches based on machine vision technology are proposed to get the sub-pixel location of black-spots. In this method, feature area is recognized based on the identification of spots' edge characteristics. The method of circle fitting is used to get positions of the spots' center. The experiments show that this system can realize the automatic identification for black spot's feature and center in sub-pixel. The accuracy of algorithm is better, and its self-adaptability is high. It provides an necessary condition for further research of OLED defect detection.

An immune-inspired danger theory model based on fuzzy set was proposed in this article. In the model the concept of fuzzy set and degree of membership are presented in the foundation of the "danger" definition in artificial immune system. By carrying on the computation to the degree of danger, it makes the organism to apperceive the danger and simultaneously to make a strategy efficiently. It improves the organism to recognize the "danger" effectively, and then enhances the rate of intrusion detection based on the artificial immune model, and reduces the false alarm.