Trilingual 3D Script Identification and Recognition using Leap Motion SensorShow others and affiliations
2019 (English)In: 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), IEEE, 2019, Vol. 5, p. 24-28Conference paper, Published paper (Other academic)
Abstract [en]
Recently, the development of depth sensing technologies such as Leap motion and Microsoft Kinect sensors facilitate a touch-less environment to interact with computers and mobile devices. Several research have been carried out for the air-written text recognition with the help of these devices. However, there are several countries (like India) where multiple scripts are used to write official languages. Therefore, for the development of an effective text recognition system, the script of the text has to be identified first. The task becomes more challenging when it comes to 3D handwriting. Since, the 3D text written in air is consists of single stoke only. This paper presents a 3D script identification and recognition system written in three languages, namely, Hindi, English and Punjabi using Leap motion sensor. In the first stage, script identification was carried out in one of the three language. Next, Hidden Markov Model (HMM) was used to recognize the words. An accuracy of 96.4% was recorded in script identification whereas accuracies of 72.99%, 73.25% and 60.5% were recorded in script identification of Hindi, English and Punjabi scripts, respectively.
Place, publisher, year, edition, pages
IEEE, 2019. Vol. 5, p. 24-28
Series
International Conference on Document Analysis and Recognition Workshops (ICDARW)
Keywords [en]
Air-writing, Leap motion, Word recognition, Script Identification, HMM
National Category
Computer Sciences
Research subject
Machine Learning
Identifiers
URN: urn:nbn:se:ltu:diva-77257DOI: 10.1109/ICDARW.2019.40076ISI: 000518786800005Scopus ID: 2-s2.0-85114108903ISBN: 978-1-7281-5054-3 (electronic)OAI: oai:DiVA.org:ltu-77257DiVA, id: diva2:1381749
Conference
2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 20-25 september, 2019, Sydney, Australia
2019-12-272019-12-272023-09-05Bibliographically approved