Abstract In this paper, the color index based thresholding method for background and foreground segmentation of plant images is presented. The proposed method is implemented with color index approach, for this purpose two color indexes are modified to provide better information about the green color of the plants. Two fixed threshold methods are proposed for the color indexes to discriminate between foreground (green plant) and background (soil). Three versions of the proposed method are presented, these are applied in plant images with controlled conditions and crop images with real environmental conditions. Experimental results demonstrate that the proposed method outperforms other algorithms used as comparative in plant images obtaining a segmentation error of 6.62 ± 5.85% and a classification ratio of 1.93 ± 0.05. Also, the proposed method provides better segmentation results in comparison with other well-known state-of-art algorithms in different crop images. Finally, the proposed method does not require of complex calculus and their implementations are straightforward on any device.

中文翻译：

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基于颜色索引的植物图像背景和前景分割阈值方法

摘要 本文提出了一种基于颜色索引的植物图像背景和前景分割阈值方法。所提出的方法是通过颜色索引方法实现的，为此目的，修改了两个颜色索引以提供有关植物绿色的更好信息。针对颜色指标提出了两种固定阈值方法来区分前景（绿色植物）和背景（土壤）。提出了所提出方法的三个版本，这些版本应用于具有受控条件的植物图像和具有真实环境条件的作物图像。实验结果表明，所提出的方法优于在植物图像中用作比较的其他算法，获得了 6.62±5.85% 的分割误差和 1.93±0.05 的分类率。还，与其他众所周知的最新算法相比，所提出的方法在不同的裁剪图像中提供了更好的分割结果。最后，所提出的方法不需要复杂的微积分，并且它们的实现在任何设备上都很简单。