沈阳农业大学学报2016，Vol.47Issue(5)：634-640,7.
基于高光谱成像的苹果病害无损检测方法
Nondestructive Detection Method of Hyperspectral Imaging for Apple Disease
摘要
Abstract
Disease is easy to occur in apple fruit. Traditional detection of apple disease is not adapted to the requirement of apple grading on-line detection. In order to achieve the fast, effective online detection for the disease apple, hyperspectral imaging was adopted to study the nondestructive detection of the anthracnose, bitter pox disease and black fruit rot and leaf spot disease in Hanfu apple. According to the relative reflectance spectrum difference between disease area and normal area, the improved manifold distance method was proposed. The total improved manifold distance L value was comprehensive calculated by the relative reflectance spectra of the disease and normal area, disease with stem/calyx area, normal and stem/calyx area. So three feature wavelengths were selected respectively from the whole band wavelength, 700, 765, 904nm. In order to get the mask image, the image of the characteristic wave band at 700 nm was threshold segmented. The interested area was extracted after secondary threshold segmentation of the mask image. The relative reflectance spectra of the three characteristic wave bands were combined, respectively, as the BP neural network input vector, to detect whether apple fruit was diseased. Finally, the relative reflectance spectra under 700 nm to 904 nm band were selected as the best combination by comparing the detection results. A recognition rate of the normal apples and diseased apples respectively were 96.25%. Results showed that the two characteristics of band obtained by hyperspectral imaging technology can effectively detect disease for apple and provide the reference for the development of multispectral imaging of appleˊs quality detection and classification system.关键词
改进流形距离/苹果病害/高光谱成像/无损检测/BP神经网络Key words
improved manifold distance/apple diseases/hyperspectral imaging/nondestructive detection/back propagation neural network分类
农业科技引用本文复制引用
刘思伽,田有文,冯迪,张芳,崔博..基于高光谱成像的苹果病害无损检测方法[J].沈阳农业大学学报,2016,47(5):634-640,7.基金项目
辽宁省大型仪器设备共享服务项目(LNDY201501003) （LNDY201501003）
