Research on the Characteristics of Light Sources in Machine Vision


  • Qiming Yuan
  • He Zhang



Machine vision, Light source, Characteristic.


A machine vision system as eyes, through image taking device will get signal converted into image signal, and then through computer processing, get the useful information for subsequent research. In the machine vision system, the stand or fall of lighting light source directly affects the system input. A good lighting solution can greatly reduce the later image processing of the computing workload, and can also reduce the cost of the system to a certain extent, so for machine vision system, the light source properties research is particularly important. Light source characteristics research mainly around the type of light source, light source, the intensity of the light source, the number of the layout of the light source and the color of the light source study of five aspects. These five factors will directly affect the lighting effect is good or bad, or even to a certain extent determines the success or failure of a complete set of machine vision system. Combine five factors analysis, find a lighting effect is the best plan combination, light source characteristics research of machine vision system is the key. In this paper, it chooses the best lighting scheme for the school logo box, use the control variable method to carry out research, respectively find the best light source type, quantity, intensity, layout and color, and then combine a set of best lighting scheme. In the lighting scheme studied in this paper, the best combination of lighting scheme is to use two red LED bulbs with 7W power to illuminate in the forward lighting position.


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Jin Weiguo, Zhou Li. Research on light source characteristics of machine vision system using MATLAB [J]. Special equipment for electronic industry, 2012,41 (02): 40-47.

Xu Lei. Development status and Prospect of machine vision technology [J]. Equipment management and maintenance, 2016 (09): 7-9.

Chen Ying. Research on development status and application dynamics of machine vision technology [J]. Wireless Internet technology, 2018, 15 (19): 147-148.

Yin Zhongxin, Wang Quanliang. Lighting optimization design in machine vision system [J]. Microcomputer information, 2010,26 (07): 129-131.

Hou yuanshao. Selection of light source in machine vision system [J]. Journal of Luoyang Normal University, 2014,33 (08): 45-49.

Wang Wenjie. LED light source and optical characteristic detection [C]. Jiangsu metrology and testing academic papers (2011): Jiangsu metrology and testing society, 2011:177-182.

Shang Huichao, Yang Rui, Duan Mengzhen, Duan Xiaowei, Zhang Hongbin. Key technology analysis of machine vision lighting system [J]. Journal of Zhongyuan Institute of technology, 2016,27 (03): 16-21.

Bi Mingde, Sun Zhigang, Li Yesong. Fabric defect detection system based on machine vision [J]. Instrument technology and sensor, 2012 (12): 37-39 + 125.

Li Yunfeng, Han Xixi, Li Shengyang. Dimension parameter measurement of stamping parts based on machine vision [J]. Tool technology, 2015,49 (11): 95-98.

Fu Lihong. Research and development of lighting source database based on machine vision [J]. Technological innovation and application, 2019 (26): 18-19.

Liu Qing, Zhang Jinhua, Huang Junqin. Detection and classification of steel ball surface defects based on machine vision [J]. Bearing, 2013 (10): 44-48.

Wang Tianyi, Wang Xin, Cao Xingqiang, Zeng Jian, Jia Zhenzhen, Li Xiao, Yao ermin. Optimization of light source for inner packaging defect detection based on machine vision [J]. Packaging engineering, 2019,40 (17): 174-181.

Hua Zhengyang. Research on thermal imaging image recognition system based on vision technology [J]. Communication world, 2019,26 (12): 12-13.

Zhou Zitian. 3D object surface information recognition and detection system based on vision technology [J]. Communication world, 2019,26 (12): 18-19.

Ye Jiaying, Deng Fei, Wang Peixin, Zhao Daxu, Wang Yuzong, Shou Guozhong. Pearl color feature extraction and recognition based on machine vision [J]. Jiangsu Agricultural Sciences, 2019,47 (20): 226-230 + 240.







How to Cite

Research on the Characteristics of Light Sources in Machine Vision. (2022). Academic Journal of Science and Technology, 3(1), 1-6.

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