The authors would like to thank to SEDIMED (a medical diagnosis center company in Peru) who supported with a medical images database. This work was partially funded by the Fondos para la Innovacion, Ciencia y Tecnologia (FINCyT-Peru) under contract 142-10-PITEA-FINCyT and CONCYTEC-Peru with STIC-AmSud 2013 under the FERMI project.

Classification green coffee beans is one of the main tasks during the quality grading process. This evaluation is normally carried out by specialist doing a visual inspection or using traditional instruments which have some limitations. This work is focused on the implementation of a computer vision system combining a hardware prototype and a software module. The hardware was made to guarantee the controlled conditions to capture the images of green coffee beans, the software is based on computer vision algorithms in order to detect defects of the coffee beans. The novelty of our proposal is the combination of algorithms to enhance the accuracy and the high number of defects detected. We applied a White Patch algorithm as an image enhancement procedure, color histograms as feature extractor and Support Vector Machine (SVM) for the classification task. It was constituted an image beans da...