Abstract
Drop analysis technology developed rapidly, the recognition of drop fingerprint become more and more important. It discussed about drop analysis technology and the methods to recognize liquid drop fingerprint. With the self-learning, self-organizing and out-supervision, self-organizing feature map network is suitable to use in drop fingerprint recognition. By MATLAB simulation, a SOM neural network which has been trained is established. Two groups of samples are identified. The identification ratio of one group is 97.5 percent, and the other group is 95 percent. The recognition performance achieved the goal as expected.
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Li, J., Song, Q., Luo, Y., Zou, C. (2010). Drop Fingerprint Recognition Based on Self-Organizing Feature Map. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16530-6_54
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DOI: https://doi.org/10.1007/978-3-642-16530-6_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16529-0
Online ISBN: 978-3-642-16530-6
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