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Mean-shift-based color segmentation of images containing green vegetation

文献类型: 外文期刊

作者: Zheng, Liying 1 ; Zhang, Jingtao 2 ; Wang, Qianyu 2 ;

作者机构: 1.Harbin Engn Univ, Sch Comp Sci & Technol, Harbin 150001, Peoples R China

2.Heilongjiang Acad Agr Sci, Hejiang Inst Agr Sci, Jiamusi 154007, Peoples R China

期刊名称:COMPUTERS AND ELECTRONICS IN AGRICULTURE ( 影响因子:5.565; 五年影响因子:5.494 )

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收录情况: SCI

摘要: Separating green vegetation in color images is a complex task especially when there are noises and shadows in the images. Our objective is to improve the segmentation rate of the images containing green vegetation by introducing a mean-shift procedure into the segmentation algorithm. The proposed algorithm mainly consists of two stages--feature extraction and image segmentation. At the first step, multiple color features, such as hue and saturation in HSI color space were extracted, as well as red,green and blue value in RGB color space. At the second step, with the extracted features, mean-shift segmentation algorithm and a BPNN, the image was classified into two parts: green and non-green vegetation. The algorithm's performance was assessed on 100 images, which were acquired under field conditions, covering different plant types, illuminations, and soil types. The test showed that the median of mis-segmentation of green and non-green vegetation of proposed method is about 4.2%.

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