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Improved Multi-objective Genetic Algorithm Based on Parallel Hybrid Evolutionary Theory
Zou Yingyong,Zhang Yongde,Li Qinghua,Jiang Jingang,Yu Guangbin 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.1
Based on the analysis on the basic principles and characteristics of the existing multi-objective genetic algorithm (MOGA), an improved multi-objective GA with elites maintain is put forward based on non-dominated sorting genetic algorithm (NSGA). NSGA-II algorithm theory and parallel hybrid evolutionary theory is described in detail. The design principle, process and detailed implementations of the improved MOGA are given. IMNSGA-II algorithm and NSGA-II algorithm are applied to test the performance of the two algorithms for different test function, experiments of example are preformed. Experimental results show that the improved MOGA achieved the optimal between the convergence and diversity.
Research on Algorithm for Automatic License Plate Recognition System
Zou Yingyong,Zhai Jian,Zhang Yongde,Cao Xinyan,Yu Guangbin,Chen Juhui 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.1
License plate recognition belongs to the field of computer vision and pattern recognition, and plays an important role in the field of intelligent transportation. The license plate location is a key technology in license plate recognition, the accurate positioning of a license or not directly affects the accuracy of character segmentation and character recognition, and has a direct impact on the efficiency of the license plate recognition system. In this paper, based on knowledge acquisition and knowledge reduction ability of rough set, as well as learning ability and generalization ability of neural network, a plate positioning system is constructed. On this basis, combined the rough set with neural networks and fuzzy logic, a rough fuzzy neural network recognition is proposed. The experimental results show that this system not only simplifies the structure of the system, but also improves the generalization capability of knowledge, and improves the accuracy of character positioning.
Study on Money Number Recognition Arithmetic
Yingyong Zou,Hongli Yu 보안공학연구지원센터 2014 International Journal of Multimedia and Ubiquitous Vol.9 No.11
Money number recognition refers to the money of the currency, the currency and authenticity recognition. Money number recognition system is the kernel module of self-service system, and the major applied range is cash-related equipments. In this paper we design a kind of money number recognition system. The quick positioning of money number is achieved based on gray value accumulation. The edge line of money number area is detected using the least square method. Using geometrical rotation method and gray adjacent interpolation method to realize the number of tilt correction. Based on the character structure characteristic and the imaginary line and character of the point of intersection features, formation recognition judgment tree, realized the character recognition. The simulation experiment indicates that this algorithm has a high recognition accuracy under the condition of rejection.
Research of Chinese Handwritten Text Segmentation Algorithm
Zou Yingyong,Zhang Yongde,Cao Xinyan,Yu Guangbin 보안공학연구지원센터 2014 International Journal of Multimedia and Ubiquitous Vol.9 No.12
OCR is a complicated process, there are many factors that can influence the recognition rate. Early period people tried to optimize the classifier to obtain high recognition rate, but the premise is that there is only one character no matter print or handwritten. For the performance of classifier has been promoted a lot, recognition rate for single character is high enough for commercial use. With the development of the demand for handwritten text recognition, how to raise the recognition rate of OCR system becomes very important. Unlike OCR system for print which focus on classifier. The research of OCR system for handwritten text is mainly on character segmentation. Statistical analysis showed that the mistake made by missegment is more than the mistake made by classifier. This is decided by the feature of handwritten text. There are more randomness and the lines are not horizontal, besides that, handwritten Chinese characters are more like overlapped and the gaps between characters are smaller. So this is the difficulty of handwritten Chinese characters. In this paper, the mutil-step searching nonlinear line exaction algorithm the paper proposed is easy and the accuracy is high, which can tackle the some weaknesses of direct projection method and indirect projection.