Abstract
In this work it is proposed an intelligent vision-based system for automatic classification of beans most consumed in Brazil. The system is able to classify the grains contained in a sample according to their skin colors, and is composed by three modules: image acquisition and pre-processing; segmentation of grains and classification of grains. In the conducted experiments, we used an apparatus controlled by a PC that includes a conveyor belt, an image acquisition chamber and a camera, to simulate an industrial line of production. The results obtained in the performed experiments indicate that the proposed system could be applied to visual quality inspection of beans produced in Brazil, since one of the steps in this process is the measurement of the mixture contained in a sample, taking into account the skin color of grains, for determining the predominant class of product and, consequently, its market price.
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Acknowledgments
The authors would like to thank UNINOVE, FAPESP–São Paulo Research Foundation by financial support (#2014/09194-5) and CNPq–Brazilian National Research Council for the scholarship granted to S. A. Araújo (#311971/2015-6).
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Belan, P.A., Araújo, S.A., Alves, W.A.L. (2016). An Intelligent Vision-Based System Applied to Visual Quality Inspection of Beans. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_89
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