Handwritten Text Digitization System implementing Google Vision API

Resumen

Image processing, together with pattern recognition, have been areas of study exploited in
recent years, achieving advances such as object classification, face recognition and text
recognition. In particular, the latter allows handwritten, typewritten or printed texts to be
converted into editable digital texts. This paper describes the design and operation of a
handwritten text digitization system, through the implementation of the Google Vision API,
oriented to Android devices. The objective of the research is to verify if its use increases the
efficiency when recognizing autograph text due to the poor performance of Optical Character
Recognition (OCR) systems when processing texts of this type. The developed system
consists of three modules: 1) Image acquisition, 2) API consumption request and 3)
Digitization of the generated OCR. For the evaluation of its performance, eleven document
formats corresponding to the areas of education, health and industry were used, and four
different image conditions (with respect to quality adjustment and area of interest cropping),
as well as a comparison with some of the existing applications on the market. Based on the
above, the average recognition of the handwritten words was calculated with respect to those
contained in each format used and a 67% efficiency of the system was determined.