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基于YUV顏色模型的番茄收獲機(jī)器人圖像分割方法
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江西省教育廳青年科學(xué)基金資助項目(GJJ10257)


Image Segmentation Method Based on YUV Color Space for Tomato Harvesting Robot
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    摘要:

    在研究番茄收獲機(jī)器人對目標(biāo)圖像分割識別時,經(jīng)常由于采集的圖像受光照影響以及分割識別算法的計算復(fù)雜性而影響到識別的準(zhǔn)確性和實時性。通過比較RGB、HSI、YUV等顏色模型的特點,從理論上分析了YUV顏色模型應(yīng)用于收獲機(jī)器人視覺系統(tǒng)的可行性,提出了一種基于YUV顏色模型的成熟番茄分割方法。同時綜合實驗及經(jīng)驗確定了成熟的紅色番茄在RGB、HSI、YUV顏色模型中閾值范圍,采用直接確定色差閾值的雙閾值分割算法識別成熟番茄,并對3種顏色模型在不同的光照條件下的分割識別效果進(jìn)行實驗對比。實驗結(jié)果證實,將基于YUV顏色模型成熟番茄分割方法應(yīng)用于番茄收獲機(jī)器人視覺識別系統(tǒng),能很好地解決其魯棒性和實時性問題。

    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. 

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林偉明,胡云堂.基于YUV顏色模型的番茄收獲機(jī)器人圖像分割方法[J].農(nóng)業(yè)機(jī)械學(xué)報,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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  • 在線發(fā)布日期: 2012-12-13
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