Evaluating the quality of a person's calligraphy using image recognition

Avila Cordova A.W.; Flores Choque A.; Paucar Nunez J.C. · International Journal of Advanced Computer Science and Applications (2020) · DOI: 10.14569/ijacsa.2020.0110890

Resumen

The problem of not developing good handwriting as a child has serious consequences for learning, these range from training human memory to the capacity for innovation. To assess the quality of a person's handwriting, it is necessary to process large amounts of images and with current improvements in machine learning this process is increasingly precise, but the development of these algorithms is complicated. For this reason, this article presents the proposal developed to evaluate the quality of a person's handwriting through image recognition in order to assist in its improvement, but performing image processing in a practical way. This evaluation will be carried out on a group of university students from the Arequipa region, in Peru, using an image processing system that allows character recognition. According to the degree of proximity, the level of handwriting will be determined in a quantified way in percentage degrees. The tests carried out show that the quality of calligraphy in university students in the Arequipa region varies between low and medium.

Instituciones: Universidad Nacional de San Agustín de Arequipa