Real-time classification of coffee fruits using FPGA (2015)
The goal in this work was to design a circuit that could classify objects by color in real-time that can be used for quality improvement. A circuit that performs color analysis of an image and, according to that analysis, classifies the object was designed. A histogram of the Spherical Coordinate Transform of the image is computed and compared to histogram patterns to make a classification decision. The circuit was tested on the classification of coffee fruits in four maturity stages: immature, under-mature, mature and over-mature. The results showed that it is possible to build a system for color object classification that works in real-time and that can be affordable and portable. The designed circuit is implemented on a Field Programmable Gate Array (FPGA), acquires video at 64 frames per second, classifies the coffee fruits at a rate of 25 fruits per second and achieved an average efficacy of 75.7%