Study on the Improvement of Color Image Enhancement Algorithm for Robot Vision System

Abstract:

Under the influence of external dynamic lighting or outdoors strong light, image color have a great influence on rapid and accurate positioning of the robot, which requires the robot vision system to obtain the high quality of color image. This paper uses the image pixel conversion ratio algorithm to improve the image recognition algorithm of robot vision system, and the use of multi threshold segmentation technology carries out restructure for image, it can get the high resolution image enhancement effect. In order to realize the algorithm, the form of using VB programming carries out algorithm implementation, and then the image enhancement can calculate the enhanced results table of image color curve distribution and different segmentation threshold image resolution. From the simulation results, this algorithm can enhance the image color effect, which provides technical support for the development and design of robot vision system.

• Periodical: Applied Mechanics and Materials (Volumes 651-653)
• Pages: 880-884
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.651-653.880
• Online since: September 2014
• Authors: Yun Zhao*
• Keywords: Color Enhancement, Pixel, Rapid Positioning, Robot, VB Program, Visual System

References

[1] Jiang Yunzhi, Hao Zhifeng. Automatic multi threshold image segmentation based on block sampling and genetic algorithm [J]. Journal of Computer Aided Design & Computer Graphics, 2011, 23 (11): 1861-1863.

[2] Jiang Lianhua, Gan Zhaohui. Review of multi target tracking [J]. Computer systems application, 2010, 19 (12): 271-273.

[3] Zhang Ling, Wang Ying. The design of CAI courseware based on constructivism theory [J]. Chinese audio-visual education, 2011, 16 (2): 41-42.

[4] Lei Fumin. Analysis of computer software development process in the sports field [J]. Journal of Xi'an Physical Education University, 2013, 20 (2): 113-114.

[5] Zhou Jun, Wang Renli, Wu Yundong. Extracting classification method linear based on edge detection [J]. Journal of Institute of Surveying and mapping, 2012, 25 (3): 181-183.

[6] Zhang Xiaolin. Image edge detection technology [J]. Application of electronic technology, 2011 (1): 38-40.

[7] Tang Yangshan, Li Jiang, Zhang Jian, Xu Jun. Research on the scene photography camera calibration [J]. Journal of Changchun science and technology University, 2011, 28 (3): 64-66.

[8] Tan Xiaojun, Yu Zhi, Li Jun. An improved calibration cameras stereo method [J]. Journal of surveying and mapping 2011, 35 (2): 138-142.

[9] Ding Ying, Li Wenhui. The medical image registration algorithm based on multi-scale Harris corner SAM [J]. Journal of China image and graphics, 2010, 15 (12): 1762-1768.

[10] Ma Lingfei, Meng Zhaopeng. Application of image registration in the image processing of traditional Chinese medicine patch [J]. Computer engineering and application, 2011, 47 (20): 155-158.

[11] Li Zezhou, Ouyang Jianquani. Video clip retrieval method based on video fingerprint [J]. Computer Engineering, 2010, 36 (7): 239-241.

[12] Zhou Aijun, Du Yuren. Video image of Harris corner detection based on vehicle recognition [J]. Journal of Yangzhou University, 2011, 11 (1): 67-70.