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	Outfield experiment of semiconductor laser jamming on color CCD camera 期刊论文 OAI收割 Optik, 2018, 卷号: 173, 页码: 185-192 作者: Tang, W.; Wang, R.; Wang, T. F.; Guo, J. \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2019/09/17 Laser jamming Color CCD camera Semiconductor laser Optical saturation and crosstalk Optics
	Visual Flame Monitoring System Based on Two-Color Method 期刊论文 OAI收割 JOURNAL OF THERMAL SCIENCE, 2009, 卷号: 18, 期号: 3, 页码: 284-288 作者: Jiang, Fan; Liu, Shi; Liangi, Shiqiang; Li, Zhihong; Wang, Xueyao 收藏 \| 浏览/下载：32/0 \| 提交时间：2015/12/18 Two-color method CCD camera Flame temperature fields Digital image processing
	Study on chromaticity balance for LED exposure system (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2007 - Laser, Ultraviolet, and Terahertz Technology, September 9, 2007 - September 12, 2007, Beijing, China 作者: Meng Z.; Meng Z. 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/03/25 A standard white light compounding algorithm based on combination of CCD illumination acquisition with computer control is presented for LEDs. The computer adjust and control the working current of LEDs by using three-color LEDs illumination acquired by CCD camera achieved chromaticity coordinates error between compounded white light and standard white light D65 less than the threshold beforehand setted by this technique then acquiring needed standard white light. Compounded white light meet the chromaticity error demand that is able to be changed at the same time the CCD illumination acquisition system is eliminated. The proposed algorithm improved the light energy utilization efficiency of LED and eliminated the offset of central wavelength and chromaticity coordinates due to work current change of LEDs. Experimental results show that the proposed algorithm achieved lesser chromaticity error uv=0.001 relative to standard white light D65 enhanced chromaticity uniformity of illumination field.
	Study on color model conversion for camera with neural network based on the combination between second general revolving combination design and genetic algorithm (EI CONFERENCE) 会议论文 OAI收割 ICO20: Illumination, Radiation, and Color Technologies, August 21, 2005 - August 26, 2005, Changchun, China 作者: Li Z.; Zhou F.; Wang C.; Li Z. 收藏 \| 浏览/下载：36/0 \| 提交时间：2013/03/25 Munsell color system is selected to establish the mutual conversion between RGB and Lab* color model for camera. The color luminance meter and CCD camera synchronously measure the same color card XYZ value is gotten from the color luminance meter the training error is 0.000748566 it can show that the method combining second general revolving combination design with genetic algorithm can optimize the hidden-layer structure of neural network. Using the data of testing set to test this network and calculating the color difference between forecast value and true value the color picture captured from CCD camera is expressed for RGB value as the input of neural network and the Lab* value converted from XYZ value is regarded as the real color value of target card which the difference is not obvious comparing with forecast result the maximum is 5.6357 NBS namely the output of neural network. The neural network of two hidden-layers is considered the minimum is 0.5311 NBS so the second general revolving combination design is introduced into optimizing the structure of neural network and the average of color difference is 3.1744 NBS. which can carry optimization through unifying project design data processing and the precision of regression equation. Their mathematics model of encoding space is gained and the significance inspection shows the confidence degree of regression equation is 99%. The mathematics model is optimized by genetic algorithm optimization solution is gotten and function value of the goal is 0.0007168. The neural network of the optimization solution is trained