Early Detection of Bruises on Apples Using Near-infrared Hyperspectral Image

摘要

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%.