食品科学2017，Vol.38Issue(8)：277-282,6.DOI:10.7506/spkx1002-6630-201708043
采用二次连续投影法和BP人工神经网络的寒富苹果病害高光谱图像无损检测
Hyperspectral Imaging for Nondestructive Detection of Hanfu Apple Diseases Using Successive Projections Algorithm and BP Neural Network
摘要
Abstract
In order to provide a theoretical basis for the online,rapid and nondestructive detection of apple diseases,hyperspectral imaging was adopted to study the nondestructive detection of diseases (mainly anthracnose,bitter pox disease,black fruit rot and leaf spot disease) in fruits of the apple cultivar ‘Hanfu’,which is widely planted in north China.The acquired hyperspectral images were used for segmentation of regions of interest and extraction of spectral information.Then,10 feature wavelengths (502,573,589,655,681,727,867,904,942 and 967 nm) were extracted in the full wavelength range of 500-970 nm by successive projection algorithm (SPA1).Furthermore,three wavelengths (681,867 and 942 nm) were selected out of these feature wavelengths by using this algorithm again (SPA2).Finally,the spectral data in the full wavelength range and at the feature wavelengths obtained after each selection step were used as input vector to build a linear discriminant analysis (LDA) model,a support vector machine (SVM) model and a BP artificial neural network (BPANN) model for the detection of diseases in apple.Analysis of the test results revealed that SPA2-BPANN was finally chosen as the best detection method,providing a correct detection rate of 100％ for both training validation sets.Our results show that hyperspectral imaging allows effective detection of diseases in apples,and the characteristic wavelength obtained can provide a reference for the development of multispectral imaging for apple quality detection and classification system.关键词
高光谱成像/连续投影法/BP人工神经网络/苹果病害/无损检测Key words
hyperspectral imaging/successive projections algorithm/BP artificial neural network/apple disease/nondestructive detection分类
农业科技引用本文复制引用
刘思伽,田有文,张芳,冯迪..采用二次连续投影法和BP人工神经网络的寒富苹果病害高光谱图像无损检测[J].食品科学,2017,38(8):277-282,6.基金项目
辽宁省大型仪器设备共享服务项目(LNDY201501003) （LNDY201501003）
沈阳市大型仪器设备共享服务专项(F15-166-4-00) （F15-166-4-00）
