In the present study, a machine vision based, online sorting system was developed, the aim
being to sort Date fruits (Berhee CV.) based at different stages of maturity, namely Khalal, Rotab and
Tamar to meet consumers’ demands. The system comprises a conveying unit, illumination and capturing
unit, and sorting unit. Physical and mechanical features were extracted from the samples provided,
and the detection algorithm was designed accordingly. An index based on color features was
defined to detect Date samples. Date fruits were fed on a conveyor belt in a row. When they were
at the center of the camera’s field of view, a snapshot was taken, the image was processed immediately
and the maturity stage of the Date was determined. When the Date passed the sensor, positioned at
the end of the conveyor belt, a signal was sent to the interface circuit and an appropriate actuator,
driven by a step motor, was actuated, leading the Date toward an appropriate port. For validation
of proposed system performance, entire samples were again sorted by experts visually. Detection rate
of the system for Tamar and Khalal was satisfactory. Although the detection rate was insufficient for
the Rotab stage, there was no a significant difference between system accuracy and that obtained by
the experts. The speed of image processing system was 0.34 s. System capacity was 15.45 kg/h.