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	The effects of image set size and time pressure on human performance and mental workload in a cyber image search task 会议论文 OAI收割 57th Human Factors and Ergonomics Society Annual Meeting - 2013, HFES 2013, San Diego, CA, United states, September 30, 2013 - October 4, 2013 作者: Zhao, Guozhen; Wu, Changxu 收藏 \| 浏览/下载：26/0 \| 提交时间：2017/07/11 Endogenous eye blinks Graphical information Heart rate variability Human performance Mental workload Physiological indices Search accuracy Subjective rating
	Handwritten Chinese Text Recognition by Integrating Multiple Contexts 期刊论文 OAI收割 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2012, 卷号: 34, 期号: 8, 页码: 1469-1481 作者: Wang, Qiu-Feng; Yin, Fei; Liu, Cheng-Lin 收藏 \| 浏览/下载：40/0 \| 提交时间：2015/08/12 Handwritten Chinese text recognition confidence transformation geometric models language models refined beam search candidate character augmentation maximum character accuracy training
	The registration of aerial infrared and visible images (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Educational and Information Technology, ICEIT 2010, September 17, 2010 - September 19, 2010, Chongqing, China 作者: Liu J.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：28/0 \| 提交时间：2013/03/25 In order to solve the registration problem of different source image existed on aerial image fusion algorithms based on Particle Swarm Optimization (PSO) are applied as search strategy in this paper and Alignment Metric (AM) is used as judgment. This study has realized the different source image registration of infrared and visible light with high speed high accuracy and high reliability. Basically with little restriction of gray level properties a new alignment measure is applied which can efficiently measure the image registration extent and tolerate noise well. Even more the intelligent optimization algorithm - Particle Swarm Optimization (PSO) is combined to improve the registration precision and rate of infrared and visible light. Experimental results indicate that the study attains the registration accuracy of pixel level and every registration time is cut down over 40 percent compared to traditional method. The match algorithm based on AM solves the registration problem that greater differences between different source images are existed on gray and characteristic. At the same time the adoption of combining the intelligent optimization algorithms significantly improves the searching efficiency and convergence speed of the algorithms and the registration result has higher accuracy and stability which builds up solid foundation for different source image fusion. The method in this paper has a magnificent effect and is easy for application and very suitable for engineering use. 2010 IEEE.
	Displacement estimation by the phase-shiftings of fourier transform in present white noise (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wu Y.-H. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 Displacement estimation is a fundamental problem in Real-time video image processing. It can be typically approached by theories based on features in spatial domain. This paper presents an algorithm which improves the theory for estimating the moving object's displacement in spatial domain by its Fourier transform frequency spectrum. Because of the characters of Fourier transform the result is based on all the features in the image. Utilizing shift theorem of Fourier transform and auto-registration the algorithm employs the phase spectrum difference in polar coordinate of two frame images sequence with the moving target1 2. The method needn't transform frequency spectrum to spatial domain after calculation comparing with the traditional algorithm which has to search Direc peak and it reduces processing time. Since the technique proposed uses all the image information including all the white noise in the image especially and it's hard to overcome the aliasing from noises but the technique can be an effective way to analyze the result in little white noise by the different characters between high and low frequency bands. It can give the displacement of moving target within 1 pixel of accuracy. Experimental evidence of this performance is presented and the mathematical reasons behind these characteristics are explained in depth. It is proved that the algorithm is fast and simple and can be used in image tracking and video image processing.