Xinman Zhang
ABSTRACT
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.
- Li, Y., Zhang, X. D., and Bao, Y. L. 2012. Method based on feature template matching to identify special icons in map. Journal of Electronic Measurement and Instrument (Jul. 2012), 605--609Google Scholar
- Wang, J., Wang, H. L., Xiang, M. SH., et al. 2012. Subpixel accuracy central location of circle target based on nonmaximum suppression. Chinese Journal of Scientific Instrument (Jul. 2012), 1460--1468Google Scholar
- Zhang, H. P. and Wang, Z. Y. 2011. Car license plate location algorithm based on intensity variance and edge density. Chinese Journal of Scientific Instrument (May 2011), 1095--1102Google Scholar
- Huang, U.B., Zhu, Q.Y., and Sicw, C. K. 2002. Extreme learning machine: A new learning scheme of feedforward neural networks, IEEE international Joint Conference on Neural Networks (Feb. 2002), 985--990.Google Scholar
- Huang, U. B., Chen, L., and Sicw, C. K. 2006. Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE Transactions on Neural Networks (Apr. 2006), 879--892. Google ScholarDigital Library
- Yuan, C. L., Xiong, Z.L., Zhou, X. H., and Peng, X. H. 2009. Study of Infrared Image Edge Detection Based on Sobel Operator. Laser & Infrared (Jan. 2009), 85--87.Google Scholar
- Kwon, O.-K., Sim, D.-G., Park, R.-H. 2001. Robust Hausdorff Distance Matching Algorithms Using Pyramidal Structures. Pattern Recognition (2001), 2005--2013.Google ScholarCross Ref
- Grauman, K. and Darrell, T. 2005. The Pyramid Match Kernel: discriminative Classification with Sets of Image Features. In Proceedings of the IEEE International Conference on Computer Vision (2005). Google ScholarDigital Library
- Gharavi-Alkhansari, M. 2001. A Fast Globally Optimal Algorithm for Template Matching Using Low-resolution Pruning. IEEE transactions on image process (Apr. 2001), 526--533. Google ScholarDigital Library
- Tanimoto, S. L. 1981. Template Matching in Pyramids Computer Graphics and Image Processing (1981), 356--369.Google Scholar
Index Terms
- An Efficient Image-ELM-Based Chip Classification Algorithm
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