Early detection of bruises on apples using near-infrared hyperspectral image

Wenqian Huanga, Baihai Zhang*, Jiangbo Li, Chi Zhang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

Early detection of bruises on apples is important for an automatic apple sorting system. A hyperspectral imaging system with the wavelength range of 1000 to 2500nm was built for detecting bruises happened in an hour on 'Fuji' apples. Principal components analysis (PCA) was conducted on the hyperspecrtral images and the principal components images were compared. Three effective wavelengths 1060, 1329 and 1949nm were determined using the weighing coefficients plot of the best principal component (PC) image. A bruise detection algorithm based on PCA on the three effective wavelengths and a global threshold method was developed. Independent validation set of 50 intact and 50 bruised apples was used to evaluate the performance of the developed algorithm. Results show that 100% of the intact apples are correctly classified, 94% of the bruised apples are correctly recognized and the overall detection accuracy is 97%.

Original languageEnglish
Title of host publicationPIAGENG 2013
Subtitle of host publicationImage Processing and Photonics for Agricultural Engineering
DOIs
Publication statusPublished - 2013
Event3rd International Conference on Photonics and Image in Agriculture Engineering, PIAGENG 2013 - Sanya, China
Duration: 27 Jan 201328 Jan 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8761
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference3rd International Conference on Photonics and Image in Agriculture Engineering, PIAGENG 2013
Country/TerritoryChina
CitySanya
Period27/01/1328/01/13

Keywords

  • Apple
  • Bruise
  • Effective wavelength
  • Hyperspectral image
  • Principal component analysis

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