The Design of HMM-Based Banknote Recognition System

摘要：

The banknote recognition system based on hidden Markov models (HMM) is proposed. It is based on the empirical risk minimization (ERM) principle. Image preprocessing includes brightness equalization and tilt correction. In order to satisfy the high speed and reliability of the banknote processing system, the grid segmentation is used for features extraction. Analyze the experimental data and determine the number of states, iterations, and Gaussian components. The proposed banknote recognition system can be applied to classify any kinds of banknotes. More than 16,000 RMB samples are sampled by CIS (Contact Image Sensor) with 25dpi. Experimental results show that the proposed method obtained higher recognition rate than ANN and SVM.

关键词： Features Eztraction HMM ERM Banknote Recognition

作者: Gai Shan Liu Jiafeng Liu Peng Tang Xianglong

作者单位: Harbin Institute of Technology School of Computer Science and Technology Harbin,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 2635-2639

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）