An Efficient Image-ELM-Based Chip Classification Algorithm

The algorithm of classification is one of the important problems to be solved in the field of chip manufacturing, which has a great impact on the efficiency of process such as subsequent chip packaging. According to the requirement of intelligent control of chip production system, chip classification algorithm based on extreme learning machine (ELM) is studied. In this paper, we use image edge gradient information as feature vector and use ELM to classify the chip. In order to improve the speed of the algorithm, we use image pyramid to down-sample the image first. The final experimental results show that, in small-scale testing, our algorithm can achieve 100% accuracy and it is insensitive to illumination changes. When the image rotates, our method can achieve more than 93.3% accuracy.