글로버메뉴 바로가기 본문 바로가기 하단메뉴 바로가기

논문검색은 역시 페이퍼서치

> 한국농업기계학회 > 한국농업기계학회 학술발표논문집 > 25권 1호

Classification model using subset feature based on a genetic algorithm of VNIR hyperspectral imaging data for organic residuals

Classification model using subset feature based on a genetic algorithm of VNIR hyperspectral imaging data for organic residuals

( Youngwook Seo ) , ( Chansong Hwang ) , ( Moon S. Kim ) , ( Ahyeong Lee ) , ( Bal-geum Kim ) , ( Jongguk Lim ) , ( Giyoung Kim ) , ( Jaekyung Jang )

- 발행기관 : 한국농업기계학회

- 발행년도 : 2020

- 간행물 : 한국농업기계학회 학술발표논문집, 25권 1호

- 페이지 : pp.114-114 ( 총 1 페이지 )


학술발표대회집, 워크숍 자료집 중 1,2 페이지 논문은 ‘요약’만 제공되는 경우가 있으니,

구매 전에 간행물명, 페이지 수 확인 부탁 드립니다.

1,000
논문제목
초록(외국어)
Hyperspectral imaging technology has emerged as an non-destructive and reliable analysis and discriminant technology for agri-food safety assessment. The technology provides the 3D cub e data with spatial and spectral data. The size of the 3D cube data set is larger than hundreds MB (in the case of 1000 pixels × 1004 pixels × 128 bands). The real-time detection and classification technology is essential for food safety assessment. To reduce the size of data is finding the optimal bands from the whole spectral data. In this study, a genetic algorithm (GA) is implemented to find subset features from 128 wavelengths and applied to develop a classification model. On the stainless steel plate, six spinach droplets were placed on each well according to the concentrations. Original juice of spinach is 100%, and additional five levels were diluted with distilled water as follows: 1:5 (20%), 1:10 (10%), 1:20 (5%), 1:50 (2%), and 1:100 (1%), respectively. VNIR hyperspectral images were obtained using a line-scan hyperspectral imaging system and concentration prediction models were developed with multivariate analysis methods. Support vector machine with 39 selected bands using the genetic algorithm showed accuracy a s 90.65% and the kappa coefficient was 0.88. The overall accuracy of PLS-DA and LDA showed reasonable accuracy as 72.13% and 85.06%, respectively. Using feature selection such as gen etic algorithm, we can reduce the dimensionality of the 3D cube data so that it is helpful to develop a rapid and real-time classifier for food safety. VNIR (400-1000 nm) hyperspectral imaging system and chemometric classification models with sub-set data based on genetic algorithm showed a potential for developing an safety assessment technology for agro-food processing machines or facilities.

논문정보
  • - 주제 : 농학분야 > 농공학
  • - 발행기관 : 한국농업기계학회
  • - 간행물 : 한국농업기계학회 학술발표논문집, 25권 1호
  • - 발행년도 : 2020
  • - 페이지 : pp.114-114 ( 총 1 페이지 )
  • - UCI(KEPA) :
저널정보
  • - 주제 : 농학분야 > 농공학
  • - 성격 : 학술발표
  • - 간기 : 반년간
  • - 국내 등재 : -
  • - 해외 등재 : -
  • - ISSN :
  • - 수록범위 : 1996–2020
  • - 수록 논문수 : 4006