[1]CHEN Shanshan,NING Jifeng,PENG Yiwei,et al.Detection of slight bruises on apples using near-infrared hyperspectral image[J].CAAI Transactions on Intelligent Systems,2013,8(4):356-360.[doi:10.3969/j.issn.1673-4785.201304041]
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Detection of slight bruises on apples using near-infrared hyperspectral image

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 8 Number of periods: 2013 4 Page number: 356-360 Column: 学术论文—机器感知与模式识别 Public date: 2013-08-25
Title:
Detection of slight bruises on apples using near-infrared hyperspectral image
Author(s):
CHEN Shanshan;  NING Jifeng;  PENG Yiwei;  ZHANG Ye
College of Information Engineering, Northwest A&F University, Yangling 712100, China
Keywords:
hyperspectral image;  slight bruises;  apple defect detection;  band ratio;  asymmetric second difference
CLC:
TP391.41
DOI:
10.3969/j.issn.1673-4785.201304041
Abstract:
A research of apple slight bruises was conducted by using hyperspectral images, aimed at solving the difficulty of the traditional defect detection method of machine vision. This study is in part based on the fact that visible light faces great challenges on it. First, the hyperspectral images of slight bruise apples between 900 and 1700 nm are acquired by a hyperspectral imaging system. It can be found that the differences between the normal part and the bruise part are obvious. Next, we analyzed the hyperspectral images via the feature band ratio method and asymmetric second difference method to improve the divisibility of the normal part and the bruise part. Finally, the bruise parts were automatically segmented from the normal part with three defect detection methods. The experimental results show that the accuracy of detecting slight bruises on the 50 apples using asymmetric second difference method is 92%, which is higher than the principal component analysis and band ratio methods. Therefore, the work provides a new method to detect the slight bruise apples accurately.
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