Open AccessAnalysis and Recognition of Bilingual Handwritten Scripts
Author(s) -
Panyam Narahari Sastry,
Akhil Goel,
Vaishnavi Suthram
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f8538.038620
Subject(s) - scripting language , computer science , hindi , character recognition , natural language processing , character (mathematics) , artificial intelligence , handwriting recognition , reading (process) , document processing , optical character recognition , intelligent word recognition , intelligent character recognition , field (mathematics) , speech recognition , feature extraction , linguistics , image (mathematics) , philosophy , geometry , mathematics , pure mathematics , operating system
In this work, offline handwritten character recognition (HWCR) is involved, which is an open area of research for Indian languages. The recognition accuracy for HWCR is around 60% as per the literature survey. The main obstacle for the research in this area is the non-availability of a standard database. Character Recognition (CR) is an application of pattern recognition. Pattern recognition has many applications like security services, defense organizations, banking, post offices, archeological field, weather forecasting, library automation, reading aids for the visually challenged, etc. There are very less number of users for Indian languages when compared to English and hence the research for HWCR is at early stage. In this work, transform based recognition techniques are used on two languages namely Hindi and English. The best recognition accuracy obtained for the bilingual handwritten scripts is 73.33% which is in line with the existing research publications.