| 基于融合显著图与GrabCut算法的水下海参图像分割 |
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| 引用本文： | 郭传鑫,李振波,乔曦,李晨,岳峻.基于融合显著图与GrabCut算法的水下海参图像分割[J].农业机械学报,2015,46(S1):147-152. |
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| 作者姓名： | 郭传鑫 李振波 乔曦 李晨 岳峻 |
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| 作者单位： | 中国农业大学,中国农业大学;农业部农业信息获取技术重点实验室,中国农业大学,中国农业大学,鲁东大学 |
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| 基金项目： | 国家国际科技合作专项资助项目(2013DFA11320) |
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| 摘 要： | 为实现海参捕捞和海参疾病诊断的自动化，应先解决真实养殖环境下海参的图像目标分割问题。为此提出一种融合显著图模型和GrabCut算法的水下海参图像分割方法。该方法改进了传统的GrabCut算法，通过对单尺度Retinex算法分析，对水下图像进行增强，结合基于区域对比度的显著性区域检测方法和直方图均衡的方法，得到海参区域图像的部分前景和可能的背景，并以此初始化GrabCut算法的掩膜，最后进行GrabCut算法迭代，得到图像目标分割结果。通过与Otsu法、分水岭法、传统GrabCut算法对比分析表明：所提方法能够准确分割出图像中海参目标，并能克服背景噪声，保留目标图像细节，算法正确分割率达到90.13%，满足海参图像目标分割的 需要。
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| 关 键 词： | 海参 图像分割 GrabCut 显著图 Retinex |
| 收稿时间： | 2015/10/28 0:00:00 |
Image Segmentation of Underwater Sea Cucumber Using GrabCut with Saliency Map |
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| Guo Chuanxin,Li Zhenbo,Qiao Xi,Li Chen and Yue Jun.Image Segmentation of Underwater Sea Cucumber Using GrabCut with Saliency Map[J].Transactions of the Chinese Society of Agricultural Machinery,2015,46(S1):147-152. |
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| Authors: | Guo Chuanxin Li Zhenbo Qiao Xi Li Chen and Yue Jun |
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| Institution: | China Agricultural University,China Agricultural University;Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture,China Agricultural University,China Agricultural University and Ludong University |
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| Abstract: | Abstract: In order to realize the automatic harvesting of sea cucumber and diagnose the disease of sea cucumber, first, the problem of the image segmentation of sea cucumber under real aquaculture environment should be solved. In this paper, a new method of image segmentation of sea cucumber using GrabCut with saliency map was proposed. This method improved the traditional GrabCut algorithm, enhanced underwater images through the single scale Retinex algorithm. Based on global contrast based salient region detection method and histogram equalization, part of foreground and possible background of regional image of sea cucumber could be obtained, the mask of GrabCut algorithm can be initialized using this information. At last, GrabCut algorithm ran iterated to get the result of image segmentation. Experiment results proved that the proposed method can segment the sea cucumber images more accurately than the Otsu method, the watershed method and the traditional GrabCut algorithm, and overcome the background noise and preserve the details of the target image. The accuracy of the algorithm was 90.13%. |
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| Keywords: | Sea cucumber Image segmentation GrabCut Saliency map Retinex |
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