王书志,张建华,冯全.基于纹理和颜色特征的甜瓜缺陷识别[J].农业机械学报,2011,42(3):175-179.
Wang Shuzhi,Zhang Jianhua,Feng Quan.Defect Detection of Muskmelon Based on Texture Features and Color Features[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(3):175-179.
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基于纹理和颜色特征的甜瓜缺陷识别   [下载全文]
Defect Detection of Muskmelon Based on Texture Features and Color Features   [Download Pdf][in English]
  
DOI:10.3969/j.issn.1000-1298.[year].[issue].[sequence]
中文关键词:  甜瓜  缺陷检测  纹理特征  颜色特征  支持向量机
基金项目:西北民族大学中青年科研基金资助项目(X2007-008)
作者单位
王书志 西北民族大学 
张建华 中国农业大学 
冯全 甘肃农业大学 
中文摘要:为了提高硬皮甜瓜缺陷分类的正确率,提取基于纹理和颜色的综合特征,采用支持向量机分类器构造了甜瓜缺陷的自动检测系统。对甜瓜图像可疑区进行了纹理分析,提取灰度共生矩阵的4个特征参数,经过比较实验得出,对比度和角二阶矩2个参数对甜瓜瓜蒂、花萼、擦伤和霉变有明显的可区分性。在可疑区域上提取了由R、G、B分量及其算术运算组成的12种颜色特征,通过实验筛选出4种具有较好区分性的颜色特征。实验结果表明,由这些优选出的纹理与颜色特征组成的综合特征及支持向量机分类器对甜瓜缺陷的识别正确率达到92.2%。
Wang Shuzhi  Zhang Jianhua  Feng Quan
Northwest University for Nationalities;China Agricultural University;Gansu Agricultural University
Key Words:Melon, Defect detection, Texture features, Color features, SVM
Abstract:In order to improve the accuracy of muskmelon’s defect detection, an automatic defect detection system based on support vector machine (SVM) was set up by adopting complex features of texture and color. Four textural parameters and twelve color features of combinations from RGB were tested for the discriminability in stem, calyx, bruise and mildew. Through the experiments, two textural and four color features with good discriminability were selected and treated as the complex features. The results indicated that with the complex features and SVM, the accuracy of classification on muskmelons was up to 92.2%. 

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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