Categorization of chicken feet by artificial vision

Abstract

In order to implement artificial vision, check its efficiency and report on its importance through the LabVIEW program, which will contribute to support the operators in the selection of chicken feet, aiming to improve the plant productivity, as well as improving the quality of the finished product. The current status of the chicken feet categorization process and its sale to the final consumer was investigated. An adequate support structure was designed to develop the processing, verifying that all the tools and methodology have a good operation. Subsequently, the functionality of the LabVIEW 2020 software was carried out, which will detect the defects of chicken feet such as bruises, skins and calluses for their respective categorization, it was developed using different software tools with their respective programming; For this, the three defects were analyzed with a total sample amount of 14 chicken feet, of which skin remnants 2, bruises 2 and calluses 10 were classified into three groups, obtaining 81.15% efficiency. The evidence that we present above demonstrates the advantage of being able to include artificial vision in the processes of a company, in our case the operation of the LabVIEW program was used, which not only benefited the company and workers, but also due to its great functionality improves the work of the operators, being an important support every day to provide a better service to customers.