Abstract
The detection of explosives and illicit material in passengers’ luggage for the purpose of station security is an important area in public traffic security. This paper presents a method for X-ray image recognition based on fuzzy rule and parallel neural networks. Neural networks have been widely used in various fields. However, the computing efficiency decreases rapidly if the scale of neural network increases. In this paper, a new method of X-ray image recognition based on the fuzzy-neuron system is proposed. In fuzzy rules method, a test pattern may belong to several classes with different degrees. A neural networks classifier is just for one class and used to make sure if the pattern is really belonged to that class based on fuzzy rules, they are combined to obtain the recognition result. From the experience results, the new method performs well.
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Liu, D., Wang, Z. (2007). A Method of X-Ray Image Recognition Based on Fuzzy Rule and Parallel Neural Networks. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4492. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72393-6_145
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DOI: https://doi.org/10.1007/978-3-540-72393-6_145
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72392-9
Online ISBN: 978-3-540-72393-6
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