DEVELOPMENT OF A MULTISPECTRAL STRUCTURED ILLUMINATION REFLECTANCE IMAGING (SIRI) SYSTEM AND ITS APPLICATION TO BRUISE DETECTION OF APPLES

SIRI is a promising new imaging modality for enhancing quality detection of food. A liquid-crystal tunable filter (LCTF)-based multispectral SIRI system was developed and used for selecting optimal wavebands to detect bruising in apples. Immediately after impact bruising, 'Delicious', 'Royal Gala', 'Granny Smith', and 'Golden Delicious' apples were imaged by the system over the spectral region of 650 to 950 nm with 20 nm increments under sinusoidally modulated illumination at a spatial frequency of 100 cycles m(-1). Each sample was subjected to two phase-shifted sinusoidal patterns of illumination with phase offsets of 0 and 2 pi/3 that were generated by a digital light projector. For comparison, spectral images were also captured under conventional uniform illumination. Spiral phase transform, a newly developed two-phase based demodulation method, was then used to retrieve amplitude component (AC) and direct component (DC) images from the SIRI images, from which ratio images were obtained by dividing the AC images by the DC images. It was found that the uniform illumination images failed to reveal the bruises in apples, whereas bruises were distinctly visible in the ratio images, with contrast varying with wavelength. Principal component analysis (PCA) showed that seven wavelengths from 710 to 830 nm were more relevant to bruise detection. A modified Otsu thresholding method based on the between-class variance was proposed for bruise segmentation from the ratio images at each of the seven wavelengths as well as the first principal component (PC1) images, which resulted in overall detection errors of 11.7% to 14.2%. This study has shown the potential of using a multispectral SIRI system for defect detection of fruit. Further research is needed to develop a general algorithm for defect detection of apples and upgrade the system toward real-time detection.