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Received:November 23, 2013 Revised:January 03, 2014
Received:November 23, 2013 Revised:January 03, 2014
中文摘要: 为解决带式输送机输送带边缘难以提取的问题，提出了一种改进脉冲耦合神经网络（PCNN，Pulse Coupled Neural Network）与数学矢量相结合的输送带边缘检测算法. 针对PCNN模型参数较多，各个参数不易自动选取的缺点，改进了模型结构，减少了待定参数；在此基础上利用矢量法寻找输送带边缘. 实验结果表明，算法具有较强的准确性和有效性.
Abstract:To solve the difficulty of conveyor belt edge detection, an algorithm for detecting conveyor belt edge based improved pulse coupled neural network (PCNN) model and vector method is proposed. There are many structure parameters in PCNN model, and it is difficult to get the adaptive parameters. The model structure was improved, and thus the number of the parameters was reduced. On the basis of this, using vector method to search for conveyor belt edge. Experiments show that the algorithm is reliable and valid.
文章编号： 中图分类号： 文献标志码：
基金项目:宝鸡文理学院校级重点项目（ZK14087）
| Author Name | Affiliation |
| KANG Kang | Department of Computer Science, Baoji University of Arts and Sciences, Baoji 721016, China |
| Author Name | Affiliation |
| KANG Kang | Department of Computer Science, Baoji University of Arts and Sciences, Baoji 721016, China |
引用文本：
亢伉.基于改进PCNN与矢量法的输送带边缘检测.计算机系统应用,2014,23(7):165-169
KANG Kang.Conveyor Belt Edge Detection Algorithm Based on the Improved PCNN Model and Vector Method.COMPUTER SYSTEMS APPLICATIONS,2014,23(7):165-169
亢伉.基于改进PCNN与矢量法的输送带边缘检测.计算机系统应用,2014,23(7):165-169
KANG Kang.Conveyor Belt Edge Detection Algorithm Based on the Improved PCNN Model and Vector Method.COMPUTER SYSTEMS APPLICATIONS,2014,23(7):165-169
