Evaluation of internal defect and surface color of whole pickles using hyperspectral imaging

Abstract

Hyperspectral imaging operated under simultaneous reflectance (400–675 nm) and transmittance (675–1000 nm) modes was studied for non-destructive and non-contact sensing of surface color and bloater damage in whole pickles. Good and defective pickles were collected from a commercial pickle processing plant. Hyperspectral images of these pickles were obtained using a prototype of on-line hyperspectral imaging system, operating in the wavelength range of 400–1000 nm. Principal component analysis was applied to the hyperspectral images of the pickle samples for bloater damage detection. Color of the pickles was modeled using tristimulus values calculated based on the hyperspectral images. There were no differences in chroma and hue angle of good and defective pickles. The average chroma of good and defective pickles was 15.5 and 15.0, respectively, and the hue angle 94.0° and 93.8°, respectively. Transmittance images at 675–1000 nm were much more effective for internal defect detection compared to reflectance images for the visible region of 500–675 nm. An overall defect classification accuracy of 86% was achieved, compared with an accuracy of 70% by the human inspectors. With further improvement, the hyperspectral imaging system could meet the need of bloated pickles detection in a commercial plant setting.