The design of HMM-based banknote recognition system
Gai Shan, Peng Liu, Liu Jiafeng, Tang Xianglong · 2009
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 25 dpi. Experimental results show that the proposed method obtained higher recognition rate than ANN and SVM.