耿楠,于伟,宁纪锋.基于水平集和先验信息的农业图像分割方法[J].农业机械学报,2011,42(9):167-172.
Geng Nan,Yu Wei,Ning Jifeng.Segmentation of Agricultural Images Using Level Set and Prior Information[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(9):167-172.
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基于水平集和先验信息的农业图像分割方法   [下载全文]
Segmentation of Agricultural Images Using Level Set and Prior Information   [Download Pdf][in English]
  
DOI:10.3969/j.issn.1000-1298.[year].[issue].[sequence]
中文关键词:  农业图像  水平集  先验信息  图像分割
基金项目:国家自然科学基金资助项目(60975007、61003151);中央高校基本科研业务费专项资金资助项目(QN2009091)
作者单位
耿楠 西北农林科技大学 
于伟 西北农林科技大学 
宁纪锋 西北农林科技大学 
中文摘要:提出了一种基于先验信息的C—V模型并对杂草﹑小麦﹑苹果进行分割研究。根据某类农业图像的特点,把图像表示为易于分割的模型,提取模型中感兴趣目标的信息量作为先验信息,通过H分量得到初始轮廓,并以此初始化提出的模型,迭代求解水平集函数,得到收敛的目标轮廓曲线。对杂草﹑小麦﹑苹果分割结果统计分割面积正确率为0.999、0.999、0.846,面积错误率为0、0、0.125。
Geng Nan  Yu Wei  Ning Jifeng
Northwest A & F University;Northwest A & F University;Northwest A & F University
Key Words:Agricultural image  Level set  Priori information  Image segmentation
Abstract:A C—V model based on level set and prior information was proposed and was applied to segment weed, wheat and apple images. Based on the characteristics of the image, the image was represented by a model which made the image easy to segment at first, and then the data contents of a region of interest in this model were extracted as the prior information. An initial contour by hue was obtained and the proposed model by this contour was initialized, the level set function was iteratively solved. Finally, a stationary-contour was obtained. The correct rates of weed, wheat and apple were 0.999, 0.999 and 0.846 respectively and the error rates were 0, 0 and 0.125 respectively.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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