基于智能多代理的复杂场景钢坯字符切分算法

在生产线钢坯检测识别过程中,如何准确地切分生产线实际复杂场景下的钢坯端面字符是一个高度复杂的智能问题.为了解决这一复杂问题,本文提出了一种基于智能多代理者的字符切分处理方法,将分控制层中的字符区域分割与切分、区域合并、区域分裂、特征计算等功能子程序作为个体代理者,主控制层作为主控代理者对这些个体代理者根据具体需要进行统一分工协调,同时各子代理者的切分信息反馈给主控代理者作为分析、控制各子代理者的重要因素,进而完成钢坯号字符的精确切分.实验结果表明,本文提出的算法能对复杂场景中的钢坯字符完成精确的切分,具有良好的稳定性与准确性,解决了复杂场景中的钢坯字符准确切分的问题,为后续钢坯字符的识别提供了保证.

Billet Character Segmentation Based on Intelligent Multi-agent in the Complex Scene

In the process of billet detection and recognition, how to accurately divide the characters at ends of steel in the complex scene is a highly complicated intelligence problem. In order to solve this complex problem, a segmentation algorithm based on intelligent multi-agent is proposed in this paper. The algorithm takes these functions: the segmentation of characters, the combination of regions, the division of regions and the calculation of features, as the agents in the subordinate control layer. And then, these agents work in coordination with each other in the control of the master agent. Moreover, the segmentation information is fed back to the master agent to control and analyze the agents. At last, thebillet characters are divided accurately through the proposed algorithm of intelligent multi-agent. The segmentation experimental results show that the proposed algorithm divides the billet characters in the complex scene accurately and steadily. What’s more, the algorithm solves the difficult problem of the accurate segmentation of billet characters in the complex scene, and provides the guarantee for the characters recognition.