基于RGB色彩空间的油菜图像自动分割方法研究

Lipin Tan, Yu-tian Li
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引用次数: 2

摘要

植物图像的自动分割是油菜和杂草识别系统研究的重要步骤。为了克服传统阈值法在油菜灰度图像分割中的不足,提出了一种基于RGB色彩空间的油菜灰度图像自动分割方法。在RGB色彩空间中,植被G分量占主导地位,土壤背景R分量占主导地位。提出了一种将G-0.8R颜色指数与0阈值相结合的油菜图像分割方法。与传统方法相比,该方法具有更好的分割效果和更短的处理时间,满足了油菜和杂草识别系统的实时性要求。形态学操作等去噪方法可以进一步提高图像质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Rape Image Automatic Segmentation Method Based on RGB Color Space
Automatic segmentation of plant images is an important step in the research on rape and weed recognition system. In order to overcome the shortcomings of traditional threshold method in rape gray image segmentation, an automatic segmentation method based on RGB color space was proposed. In RGB color space, the G component of vegetation is dominant, and the R component of soil background is dominant. A method combining G-0.8R color index with 0 threshold is proposed to segment rape image. Compared with traditional methods, this method has better segmentation effect and shorter processing time, which meets the real-time requirements of rape and weed identification system. Morphological operations and other denoising methods can further improve the image quality.
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