A new design of olive fruit sorting machine using color image processing

Abstract

The food industry relies on a rapid and accurate separation and classification of fruits immediately after harvest before spoilage sets in. This study developed a prototype machine for olive fruit separation with image processing technology, founded on the changing hues of the olive fruit according to their level of maturity. The operating principle of the machine was based on a fruit-recognition software development using a USB3 camera functioning at 120 frames/s. Separation of the desired fruit is determined by first obtaining the color pattern from the camera image, which is then sent to the selected pattern as a clipboard and template. Detection of the fruit is then performed by comparing the color pattern of the fruit falling from a horizontal conveyor with the sinking color pattern, and location coordinates at the time of fall are determined. For image processing, an appropriate software parallel to our aim has been developed, establishing an algorithm through LabVIEW vision development. Digital output ports of a USB 6008 DAQ card were used to control the pneumatic valves. For lighting, the white LEDs were positioned at a particular angle. The separation process used pneumatic valves with a 1 ms response time. During the separation process, optimum values were determined for the primary parameters, such as the fruit falling angle with respect to the belt speed, pneumatic valve position and ideal camera angle. This prototype machine was determined to have a 98% success rate in separating olive fruit.