| 基于颜色和纹理特征的黄瓜病害识别算法 |
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| 引用本文： | 胡敏,陈红波,许良凤,谢成军,江河. 基于颜色和纹理特征的黄瓜病害识别算法[J]. 电子测量与仪器学报, 2015, 29(7): 970-977 |
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| 作者姓名： | 胡敏 陈红波 许良凤 谢成军 江河 |
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| 作者单位： | 1.合肥工业大学计算机与信息学院合肥230009；2.合肥工业大学情感计算与先进智能机器安徽省重点实验室合肥230009,1.合肥工业大学计算机与信息学院合肥230009；2.合肥工业大学情感计算与先进智能机器安徽省重点实验室合肥230009,1.合肥工业大学计算机与信息学院合肥230009；2.合肥工业大学情感计算与先进智能机器安徽省重点实验室合肥230009,中国科学院合肥智能机械研究所合肥230031,1.合肥工业大学计算机与信息学院合肥230009；2.合肥工业大学情感计算与先进智能机器安徽省重点实验室合肥230009 |
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| 基金项目： | 国家“863”计划（2012AA011103）、安徽省科技计划（1206c0805039）、国家自然科学基金（61432004）资助项目 |
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| 摘 要： | 为了提高黄瓜叶部病害的识别效果及实用性,增强特征描述能力,提出一种新的黄瓜病害图像分割及颜色、纹理特征提取算法。首先,对自然环境中采集的病害图片进行不同颜色空间的预处理和分割,对分割结果图像进行融合处理;然后,对病斑区域提取模糊量化直方图、颜色聚合度作为颜色特征,利用颜色相似性度量函数计算颜色共生矩阵,提取病斑的纹理特征;最后,通过核主成分分析对颜色和纹理特征进行融合,去除冗余成分,利用支持向量机对病害进行分类识别。在采集的黄瓜病害实验库上进行实验,取得了94.11%的识别率。通过充分利用病害识别中占主要识别依据的颜色信息,并结合纹理信息,较好地表达了病斑特征。和其他方法的实验对比结果表明,本文方法能有效提高黄瓜病害的识别率。
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| 关 键 词： | 叶部病害；模糊量化直方图；颜色聚合度；颜色共生矩阵；核主成分分析 |
Cucumber disease recognition algorithm based on color and texture features |
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| Hu Min,Chen Hongbo,Xu Liangfeng,Xie Chengjun and Jiang He. Cucumber disease recognition algorithm based on color and texture features[J]. Journal of Electronic Measurement and Instrument, 2015, 29(7): 970-977 |
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| Authors: | Hu Min Chen Hongbo Xu Liangfeng Xie Chengjun Jiang He |
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| Affiliation: | 1.School of Computer and Information, Hefei University of Technology, Hefei 230009, China;2.Hefei University of Technology, Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, Hefei 230009, China,1.School of Computer and Information, Hefei University of Technology, Hefei 230009, China;2.Hefei University of Technology, Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, Hefei 230009, China,1.School of Computer and Information, Hefei University of Technology, Hefei 230009, China;2.Hefei University of Technology, Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, Hefei 230009, China,Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China and 1.School of Computer and Information, Hefei University of Technology, Hefei 230009, China;2.Hefei University of Technology, Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine, Hefei 230009, China |
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| Abstract: | |
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| Keywords: | leaf disease fuzzy quantization histogram polymerization degree of color color co occurrence matrix kernel principal component analysis |
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