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基于MMC與CV模型的苗期玉米圖像分割算法
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Color Image Segmentation Algorithm of Corn Based on MMC and CV Model
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    摘要:

    針對苗期玉米田復(fù)雜土壤背景噪聲，提出一種基于MMC（最大間隔準則）與CV（Chan-Vese）模型的玉米彩色圖像分割算法。利用MMC對玉米彩色圖像灰度化，用TV（全變分）濾波器對灰度圖像進行去噪，用CV模型對去噪圖像進行圖像分割。試驗結(jié)果表明，算法優(yōu)于傳統(tǒng)的顏色因子與Otsu組合算法，能有效去除圖像中的小雜草和青苔，實現(xiàn)玉米目標提取，錯分率為4.32%，漏分率為9.69%，相似度為86.57%。

    Abstract:

    Aiming at removing complex soil background noise in the corn seedling filed, a color image segmentation algorithm based on MMC (Maximum margin criterion) and CV (Chan-Vese) was proposed. The corn color image was transformed into gray image by using MMC, and the grayscale image was denoised by TV (Total variation) filter. Then filtered image was segmented by the CV model. The results of the experiment by Matlab showed that the algorithm could effectively get the extraction of the objection of corn and noise reduction of weed and moss simultaneously in the image. The misclassification rate and the leakage rate were 4.32% and 9.69% respectively, and the similarity was 86.57%.

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程玉柱,陳 勇,張 浩.基于MMC與CV模型的苗期玉米圖像分割算法[J].農(nóng)業(yè)機械學(xué)報,2013,44(11):266-270. Cheng Yuzhu, Chen Yong, Zhang Hao. Color Image Segmentation Algorithm of Corn Based on MMC and CV Model[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(11):266-270.

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  • 在線發(fā)布日期: 2013-11-07
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