Automated classification system of giant white corn using image processing and supervised techniques

Abstract

Nowadays, the use of artificial vision for classification in agricultural products has proven to have a great impact on this field. The exportation of agricultural goods has risen all over the world, consequently, that is the reason why exporting companies are looking to automate their processes and artificial vision techniques seems a great niche. This automation will allow an improvement in their production performance by diminishing the time and cost of their processes. While having a sound quality product in less time, improved precision and with no extensive manipulation of the product. In this article, we aim to offer a low cost alternative to this procedure oriented to the classification of Peruvian white corn by proposing an algorithm for the segmentation and recognition of images using computer vision techniques.