Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms
Ondřej Boštík, Jan Klečka · IFAC-PapersOnLine · 2018
The focus of this paper is to compare several common machine learning classification algorithms for Optical Character Recognition of CAPTCHA codes. The main part of a research focuses on the comparative study of Neural Networks, k-Nearest Neighbour, Support Vector Machines and Decision Trees implemented in MATLAB Computing environment. Achieved success rates of all analyzed algorithms overcome 89%. The main difference in results of used algorithms is within the learning times. Based on the data found, it is possible to choose the right algorithm for the particular task.