SVM Classifier for Offline Handwritten and Printed Mathematical Expression Recognition
- DOI
- 10.2991/978-94-6463-136-4_84How to use a DOI?
- Keywords
- Offline handwritten and printed; Mathematical expression recognition; logical expressions; SVM; recognition rate
- Abstract
The recognition of Mathematical Expressions (ME) constitutes a challenging problem in character recognition research. A very few studies of offline Mathematical expressions have been so far reported in the literature. This paper focuses on offline handwritten and printed mathematical logical expressions recognition using Support Vector Machine classifier (SVM). In the work of expression recognition, the expressions were segmented into individual characters. The feature extraction method with combination of Normalized chain code and zone based density was used to get the features of a character. The present work considers logical expressions with subscripts for recognition. The experimental results for recognition rates of handwritten and printed expressions are reported. The result shows that the recognition rate of handwritten expression is 84.1% and that for printed expression is 90.3%.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Manisha Bharambe AU - Kavita Kobragade AU - Poonam Ponde PY - 2023 DA - 2023/05/01 TI - SVM Classifier for Offline Handwritten and Printed Mathematical Expression Recognition BT - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022) PB - Atlantis Press SP - 953 EP - 965 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-136-4_84 DO - 10.2991/978-94-6463-136-4_84 ID - Bharambe2023 ER -