http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
초분광 반사광 영상을 이용한 배추 종자(Brassica campestris L) 비파괴 품질 측정기술 개발
안치국 ( Chi Kook Ahn ),백인석 ( In Suck Baek ),모창연 ( Chang Yeun Mo ),강석원 ( Suk Won Kang ),김문성 ( Moon S. Kim ),조병관 ( Byoung Kwan Cho ) 한국산업식품공학회 2012 산업 식품공학 Vol.16 No.3
Cabbage (Brassica campestris L) is an important crop for Asian countries, and especially so for Korea, Japan and China. In order to achieve uniform and high-yield rates of cabbage product, seed lot quality needs to be controlled. Non-destructive evaluation of seed viability is an important technique for investigating seed quality. Hyperspectral imaging technique, which combines the features of imaging and spectroscopy, has been considered one of the most powerful nondestructive evaluation methods allowing comprehensive analysis of the physical and biochemical characteristics of materials. In this study, the feasibility of hyperspectral reflectance imaging technique was investigated for the evaluation of seed viability. For the investigation of viable and non-viable seeds, some viable seeds were artificially aged. Hyperspectral reflectance technique was used to discriminate aged cabbage seeds from normal seeds. The PLSDA and simple image threshold methods were applied to investigate the feasibility of distinguishing the aged seeds from the normal seeds. The discrimination accuracy was 96.7% for the calibration set and 96.9% for the test set. The resultant images from the PLS-DA method showed high classification performance in distinguishing the nonviable from the viable seeds, which is an impossible task by naked eye and by conventional color cameras. Hyperspectral reflectance imaging has good potential for discriminating nonviable cabbage seeds from massive amounts of viable cabbage seeds.
논문 : 정보처리 및 복합기술 ; 초분광 반사광 영상을 이용한 "후지" 사과의 멍 검출에 관한 연구
조병관 ( Byoung Kwan Cho ),백인석 ( In Suck Baek ),이남근 ( Nam Geun Lee ),모창연 ( Chang Yeun Mo ) 한국농업기계학회 2011 바이오시스템공학 Vol.36 No.6
Defects exist underneath the fruit skin are not easily discernable by using conventional color imaging technique in the visible wavelength ranges. Development of sensitive detection methods for the defects is necessary to ensure accurate quality sorting of fruits. Hyperspectral imaging techniques, which combine the features of image and spectroscopy to acquire spatial and spectral information simultaneously, have demonstrated good potentials for identifying and detecting anomalies on biological substances. In this study, a high spatial resolution hyperspectral reflectance technique was presented as a tool for detecting bruises on apple. The two-band ratio (494 nm / 952 nm) and simple threshold methods were applied to investigate the feasibility of discriminating the bruises from sound tissue of apple. The pixel wise accuracy of the discrimination was 74%. The resultant images processed with selected wavebands and morphologic algorithm distinctively showed the early stages of bruises on apple which were not discernable by naked eyes as well as a conventional color camera. Results demonstrated good potential of the hyperspectral reflectance imaging for detection of bruises on apple.
초분광 반사 영상과 부분최소제곱회귀 모델을 이용한 우유 분말에 혼합된 미량 멜라민의 함량 예측
임종국 ( Jong Guk Lim ),김문성 ( Moon S Kim ),백인석 ( In Suck Baek ),모창연 ( Chang Yeun Mo ),이호영 ( Ho Young Lee ),강석원 ( Su Kwon Kang ),이강진 ( Kang Jin Lee ),김기영 ( Gi Young Kim ) 한국산업식품공학회 2013 산업 식품공학 Vol.17 No.4
Melamine has been reported to be responsible for kidney stones and renal failure among infants and children. Conventional detection methods, High-Performance Liquid Chromatography (HPLC) and Gas Chromatography (GC), are sensitive enough to detect trace amounts of the contaminant, but they are time consuming, expensive, and laborintensive. Hyperspectral imaging methods, which combine spectroscopy and imaging, can provide rapid and nondestructive means to assess the quality and safety of agricultural products. In this study, near-infrared hyperspectral reflectance imaging combined with partial least square regression analysis was used to predict melamine particle concentration in dry milk powder. Melamine particles, with concentration levels ranging from 0.02% to 1% by weight ratio (g/g), were mixed with dry milk powder and used for the experiment. Hyperspectral reflectance images in the wavelength range from 992.0 nm to 1682.1 nm were acquired for the mixtures. Then PLSR models were developed with several preprocessing methods. Optimal wavelength bands were selected from 1454.5 nm to 1555.6 nm using beta-coefficients from the PLSR model. The best PLSR result for predicting melamine concentration in milk powder was obtained using a 1st order derivative pretreatment with Rv2=0.974, SEP=±0.055%, and F=6.