CAJ | 학술논문

苹果损伤是一种发生在水果采摘和产后处理阶段的不可避免的主要缺陷。为了快速有效地识别苹果的轻微损伤，以具有代表性的双色红富士苹果为研究对象，提出了一种以高光谱成像和最低噪声分离（MNF）变换的苹果轻微损伤识别检测方法。首先，使用高光谱成像系统获取苹果的可见-近红外波段（400～1000nm）的图像，对比发现全波段的最低噪声分离变换比主成分分析（PCA）变换可获得更好的识别效果；其次，利用I-RELIEF算法对正常表皮和损伤区域的光谱进行分析得出权值系数图，依据该系数曲线挑选出了5个特征波段（560，660，720，820和960nm）；最后，特征波段和最低噪声分离变换开发了损伤苹果的识别检测算法。利用该算法对80个正常苹果和含有不同时间阶段轻微损伤的苹果进行试验，损伤识别总体正确率为97.1％，试验结果表明，利用该方法和选取的特征波段可以快速有效地识别苹果的早期轻微损伤，为利用多光谱成像技术和最低噪声分离变换在线检测苹果轻微损伤奠定了基础。
평과손상시일충발생재수과채적화산후처리계단적불가피면적주요결함。위료쾌속유효지식별평과적경미손상，이구유대표성적쌍색홍부사평과위연구대상，제출료일충이고광보성상화최저조성분리（MNF）변환적평과경미손상식별검측방법。수선，사용고광보성상계통획취평과적가견-근홍외파단（400～1000nm）적도상，대비발현전파단적최저조성분리변환비주성분분석（PCA）변환가획득경호적식별효과；기차，이용I-RELIEF산법대정상표피화손상구역적광보진행분석득출권치계수도，의거해계수곡선도선출료5개특정파단（560，660，720，820화960nm）；최후，특정파단화최저조성분리변환개발료손상평과적식별검측산법。이용해산법대80개정상평과화함유불동시간계단경미손상적평과진행시험，손상식별총체정학솔위97.1％，시험결과표명，이용해방법화선취적특정파단가이쾌속유효지식별평과적조기경미손상，위이용다광보성상기술화최저조성분리변환재선검측평과경미손상전정료기출。
Bruising is one of the major defects occurring on apple surface inevitably during postharvest handling and processing stage .To detect slight bruises on apples fast and efficiently ,a novel bruises detection algorithm based on hyperspectral imaging and minimum noise fraction transform is proposed .First ,the hyperspectral images in the visible and near-infrared (400~1 000 nm) ranges are acquired ,and MNF transform based on full ranges could obtain better detection performance compared to PCA transform ;Second ,five wavebands (560 ,660 ,720 ,820 and 960 nm) are selected as the effective wavebands based on the coef-ficient curve of I-RELIEF method conducted on spectra extracted from intact and bruise surface ;Third ,the bruises detection al-gorithm is developed based on the effective wavebands and MNF transform method .For the investigated 40 sound samples and 40 different time stage bruise samples ,the results with a 97 .1% overall detection rate are got .The recognition results indicate that the proposed methods and the effective wavelengths selected in this paper are feasible and efficient .This research lays a foundation for the development of multispectral imaging system based on MNF transform for slight bruises detection on apples .