基于灰度关联分析的苹果病害识别方法研究  

Research on identification method of apple disease based on gray relation analysis

作　　者：霍迎秋[1] 唐晶磊[1] 尹秀珍[1] 

机构地区：[1]西北农林科技大学信息工程学院,陕西杨凌712100

出　　处：《实验技术与管理》2013年第1期49-51,55,共4页Experimental Technology and Management

基　　金：国家自然科学基金(31101075);西北农林科技大学科技创新专项重点项目(QN2011069)

摘　　要：为实现自然条件下低分辨率苹果病害的智能识别,对获取图像进行预处理,采用改进的水平集交互式分割方法提取病斑。在实验的基础上,基于灰度共生矩阵提取8个纹理特征参数作为病斑的有效识别特征,构建了基于灰度关联分析的病害识别模型。实验结果表明,用优选的8个纹理特征和基于灰度关联分析识别模型,对3种病害的平均正确识别率最高达到85.41%,可以有效识别苹果的病害。To realize intelligently identification of the apple fruit＇s disease using low- resolution image, after pre-processing, the diseased parts were extracted using improved level set interactive segmentation method. According to the experimental results, the co-occurrence matrix was used to extract eight texture characteris- tics as recognizable features. The disease identification model is constructed based on the gray relation analy- sis. Experiments show that the optimal 8 features and the gray relation analysis model have the average correct identification rate being 85.41% for the 3 kinds of diseases, which can effectively identify the apple diseases.

关 键 词：苹果病害 水平集 特征提取 图像识别 灰度关联分析 

分 类 号：S661.134[农业科学—果树学] TN911.73[农业科学—园艺学]