林伟明,胡云堂.基于YUV颜色模型的番茄收获机器人图像分割方法[J].农业机械学报,2012,43(12):176-180.
Lin Weiming,Hu Yuntang.Image Segmentation Method Based on YUV Color Space for Tomato Harvesting Robot[J].Transactions of the Chinese Society for Agricultural Machinery,2012,43(12):176-180.
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基于YUV颜色模型的番茄收获机器人图像分割方法   [下载全文]
Image Segmentation Method Based on YUV Color Space for Tomato Harvesting Robot   [Download Pdf][in English]
  
DOI:10.6041/j.issn.1000-1298.2012.12.032
中文关键词:  番茄  收获机器人  YUV颜色模型  图像分割  机器视觉
基金项目:江西省教育厅青年科学基金资助项目(GJJ10257)
作者单位
林伟明 九江学院 
胡云堂 九江学院 
中文摘要:在研究番茄收获机器人对目标图像分割识别时,经常由于采集的图像受光照影响以及分割识别算法的计算复杂性而影响到识别的准确性和实时性。通过比较RGB、HSI、YUV等颜色模型的特点,从理论上分析了YUV颜色模型应用于收获机器人视觉系统的可行性,提出了一种基于YUV颜色模型的成熟番茄分割方法。同时综合实验及经验确定了成熟的红色番茄在RGB、HSI、YUV颜色模型中阈值范围,采用直接确定色差阈值的双阈值分割算法识别成熟番茄,并对3种颜色模型在不同的光照条件下的分割识别效果进行实验对比。实验结果证实,将基于YUV颜色模型成熟番茄分割方法应用于番茄收获机器人视觉识别系统,能很好地解决其鲁棒性和实时性问题。
Lin Weiming  Hu Yuntang
Jiujiang University;Jiujiang University
Key Words:Tomato, Harvesting robot, YUV color space, Image segmentation, Machine vision
Abstract:In the research of segmentation of the target image for tomato harvesting robot, the accuracy was affected by illumination and calculation complication. Firstly, the characteristics of RGB, HIS and YUV color spaces were compared. It was theoretically analyzed that the YUV color space applying to tomato harvesting robot vision system was feasible. Then, the threshold value of the ripe tomato in their color spaces was given according to the results of experiments and experience. The double-threshold algorithm based on YUV color space was put forward to apply to the tomato harvesting robot vision system. And the experiments under different illumination were designed to segment ripe tomato respectively in RGB, HIS and YUV color space in order to test the effect of those algorithms. The experiments also showed that the algorithm based on YUV color space had the better robust and the better real-time than the others. 

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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