IC wafer defect detection using image segmentation based on cultural algorithms

Abstract

The integrated circuit (IC) design technology has made the chip density continue to increase. The high performance chips have a high sensitivity to the slightest defects in manufacturing procedure, therefore the defect detection is needed in order to ensure the performances of chip and semiconductor device. For the defects on a wafer, a detection method using image segmentation is presented in this paper. The method performs the segmentation of wafer image by selecting the threshold values. The optimal thresholds are computed by the technique based on cultural algorithm. The designs of population space, the belief space, and communication protocol in the cultural algorithm, are given in detail. An integration of genetic algorithm and simulated annealing is used to produce the new individuals in the population space. The experimental results show that the defect detection method proposed in this paper can obtain the features of defects effectively, the better image about the defect on a wafer can be obtained if the differential chart of the original image and the intact image of wafer is computed in advance.