Publication detail

Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms

BOŠTÍK, O. KLEČKA, J.

Original Title

Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms

Type

conference paper

Language

English

Original Abstract

The focus of this paper is to compare several common machine learning classi cation 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 di erence 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.

Keywords

CAPTCHA, OCR, Supervised Learning, Template Matching, Decision Trees, k-NN, SVM, Neural Network

Authors

BOŠTÍK, O.; KLEČKA, J.

Released

23. 4. 2018

Location

Ostrava

ISBN

2405-8963

Periodical

IFAC-PapersOnLine (ELSEVIER)

Year of study

2018

Number

15

State

Kingdom of the Netherlands

Pages from

208

Pages to

213

Pages count

6

BibTex

@inproceedings{BUT147094,
  author="Ondřej {Boštík} and Jan {Klečka}",
  title="Recognition of CAPTCHA Characters by Supervised Machine Learning Algorithms",
  booktitle="15th IFAC Conference on Programmable Devices and Embedded Systems - PDeS 2018",
  year="2018",
  journal="IFAC-PapersOnLine (ELSEVIER)",
  volume="2018",
  number="15",
  pages="208--213",
  address="Ostrava",
  doi="10.1016/j.ifacol.2018.07.155",
  issn="2405-8963"
}