Detection of External Damage of Apple by Hyperspectral Image Technique

被引：0
|
作者：
Liu J. [1 ]
Liu F. [1 ]
Shi T. [1 ]
Sun C. [1 ]
Zhang J. [1 ]
Men H. [1 ]
机构：
[1] Department of Automation Engineering, Northeast Electric Power University, Jilin
来源：
Journal of Chinese Institute of Food Science and Technology | 2018年 / 18卷 / 01期
关键词：
Apple; Facula noise; Hyperspectral image; Principal component analysis; Two order Butterworth high pass filter;
D O I：
10.16429/j.1009-7848.2018.01.036
中图分类号：
学科分类号：
摘要：
In this study, the image of apples was acquired with the hyperspectral sorter and the detection of external damage on apples had been achieved based on the spectral image information. The principal component analysis (PCA) was applied to extract the feature information in 640 nm in order to reduce the redundancy and correlation. Spot noise in spectral feature images caused the apple external damage detection was ineffective. So the feature of the spot in the spectral image was analyzed and the spot signal in the frequency domain of the image was suppressed and the edge image information of the damaged area was enhanced by second-order Butterworth high-pass filter. Comparing the damage detection effect, it was obviously that the characteristics of the data showed up more factually in the image after filtering.The result showed that the damage detectioneffect of the apple was more significant after Butterworth with the accuracy of95%. © 2018, Editorial Office of Journal of CIFST. All right reserved.
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页码：278 / 284
页数：6
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