Development of a structured illumination reflectance imaging system for enhanced detection of subsurface and surface defects in apple fruit

A novel method of defect detection in apple fruit was developed using structured illumination reflectance imaging (SIRI) where sinusoidal illumination patterns are projected onto samples to recover depth-specific information through varying the spatial frequency of the illumination pattern. Preliminary tests were performed on a Nylon test material using a newly constructed SIRI system and results revealed that the SIRI system was capable of detecting subsurface inhomogeneities and also enhancing sample surface features. The SIRI system was applied for detection of bruises with various severities and ages in 'Golden Delicious' and 'Delicious' apples. The SIRI images consistently outperformed the uniform illumination images, with overall detection rates ranging between 70-100% even in fresh bruises which had not yet visibly developed on the fruit surface. The SIRI system was also able to detect bruises that naturally occurred during infield sorting operations. The detection rates ranged from 81.1%-85.1% for the 'Gala' variety, and were lower at 62.7%-69.5% for 'Fuji' apples. SIRI was then applied to detect various surface defects on 'Fuji' and 'Gala' fruit. It was found that defects such as insect damage, black scab, sunburn and rot could be detected but with low detection rates. Linear discriminant analysis of the various defect types revealed that distinct features present in the SIRI images made classification of defective apples possible. The SIRI method has demonstrated its potential in successfully detecting fresh bruises and certain surface defects in apple fruit and should warrant further research into quality assessment of fresh fruit.