CAJ | 학술논문

高光谱成像技术把二维成像和光谱技术融为一体，图像技术可全面反映水果的外部品质、表面缺陷及污染等，光谱技术则可用于水果内部品质的检测，能对水果的综合品质进行全面、快速的检测。以苹果为研究对象，得用高光谱成像技术和主成分分析方法分析了苹果的风伤和压伤，对比分析不同光谱区域主成分分析对识别结果的影响，优选出识别光谱区域(550～950 nm)。通过主成分分析根据权重系数，选取了714 nm作为苹果风伤研究的最佳特征波长。
고광보성상기술파이유성상화광보기술융위일체，도상기술가전면반영수과적외부품질、표면결함급오염등，광보기술칙가용우수과내부품질적검측，능대수과적종합품질진행전면、쾌속적검측。이평과위연구대상，득용고광보성상기술화주성분분석방법분석료평과적풍상화압상，대비분석불동광보구역주성분분석대식별결과적영향，우선출식별광보구역(550～950 nm)。통과주성분분석근거권중계수，선취료714 nm작위평과풍상연구적최가특정파장。
Image cubes containing continuous spectral waveband information, in which the image information could be used for external attribute inspection while the spectral information could be applied to the internal attribute inspection,could be obtained from implementing a hyperspectral image technology which combines the advantages of computer vision and spectroscopy. Apples were adopted as the experimental object. A hyperspectral imaging system with the wavelength range of 400-1 000 nm was built for detecting bruises. The hyperspectral imaging system was used as a powerful tool to determine the effective wavelengths that could be used for the detection of bruises on apples. The optimal wavelength region 550-950 nm for bruise detection was selected by the Principal component analysis (PCA), which is a very effective method for data dimension reduction and feature extraction of the hyperspectral data cube. The effective wavelengths 714 nm with weighing coefficients at peaks was determined using the loading coefficients of the PC4 image of PCA on 400-1 000 nm.