Multispectral Method for Apple Defect Detection using Hyperspectral Imaging System

Abstract

Hyperspectral imaging is a non-destructive detection technology and a powerful analytical tool that integrates conventional imaging and spectroscopy to get both spatial and spectral information from the objects for food safety and quality analysis. A recently developed hyperspectral imaging system was used to investigate the wavelength between 530nm and 835nm to detect defects on Red Delicious apples. The combination of band ratio method and relative intensity method were developed in this paper, which using the multispectral wavebands selected from hyperspectral images. The results showed that the hyperspectral imaging system with the properly developed multispectral method could generally identify 95% of the defects on apple surface accurately. The developed algorithms could help enhance food safety and protect public health while reducing human error and labor cost for food industry