Abstract
An on-line eggplant grading machine was developed to inspect and grade fresh marketeggplant in an agriculture cooperative located at Okayama, Japan. Two machine vision systems,which made up from 6 color CCD cameras and 4 monochrome CCD cameras were used foracquiring digital image of the eggplant. Eggplant fruits are graded when the fruits were conveyedthrough these cameras on a special designed rotary tray. 180 vertical turn of the rotary tray inbetween these camera boxes enable the inspection of the eggplants entire surface. It was found thatdisorientated and disposition fruit on the rotary tray affect the grading process. Eggplant fruit is dark purple in color with extremely low spectral reflectance in the visible spectrum. Consequently, defectdetection on the eggplant fruits and extraction of fruits feature from the low color contrast backgroundare difficult. A new NIR-enhanced-color CCD camera (380nm-1400nm) was studied in overcome theproblems mentioned above. Experimental result showed that this new camera was able to extract thefruits feature from dark background and detection of low-contrast-defects was found possible too.
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