title: [Detection of slight bruises on apples based on hyperspectral imaging and MNF transform].
abstract: 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 approximately 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 coefficient curve of I-RELIEF method conducted on spectra extracted from intact and bruise surface; Third, the bruises detection algorithm 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.
authors.forename: Bao-Hua
authors.initials: BH
authors.lastname: Zhang
authors.forename: Wen-Qian
authors.initials: WQ
authors.lastname: Huang
authors.forename: Jiang-Bo
authors.initials: JB
authors.lastname: Li
authors.forename: Chun-Jiang
authors.initials: CJ
authors.lastname: Zhao
authors.forename: Cheng-Liang
authors.initials: CL
authors.lastname: Liu
authors.forename: Dan-Feng
authors.initials: DF
authors.lastname: Huang
authors.forename: Liang
authors.initials: L
authors.lastname: Gong
mesh_terms: D000465:Algorithms; D005504:Food Analysis / Q000379:methods*; D063427:Food Quality; D005638:Fruit; D027845:Malus; D013057:Spectrum Analysis