{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:01:31Z","timestamp":1777705291379,"version":"3.51.4"},"reference-count":14,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,3,2]]},"abstract":"<jats:p>Formation of Gurmukhi character\/akshara from the recognized strokes in online handwriting recognition systems is a challenging task. In this paper, the task of character and akshara formation in an unconstrained environment have been addressed. After the recognition of online handwritten strokes the Gurmukhi akshara is formed using a hybrid approach. Two classifiers, namely, Support Vector Machine (SVM) and Recurrent Neural Network (RNN) have been experimented in this study. The classifier, yielded the maximum cross-validation accuracy has been utilized for stroke recognition. A total of 52,500 word samples have been collected from 175 writers in order to train the classifiers. Three post processing algorithms have been proposed in this article for improving the character and akshara recognition accuracy. The proposed methodology when tested on a dataset of 21,500 aksharas, written by 50 new writers, achieved average the accuracy rate of 97.1% and 87.1% for base character and akshara recognition, respectively.<\/jats:p>","DOI":"10.3233\/jifs-201613","type":"journal-article","created":{"date-parts":[[2021,1,22]],"date-time":"2021-01-22T17:36:14Z","timestamp":1611336974000},"page":"4799-4809","source":"Crossref","is-referenced-by-count":0,"title":["Post-processing algorithms for the formation of online handwritten Gurmukhi character\/akshara"],"prefix":"10.1177","volume":"40","author":[{"given":"Harjeet","family":"Singh","sequence":"first","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India"}]},{"given":"R.K.","family":"Sharma","sequence":"additional","affiliation":[{"name":"Thapar Institute of Engineering and Technology, Patiala, Punjab, India"}]},{"given":"Muthukumaran","family":"Malarvel","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-201613_ref4","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.patrec.2013.08.014","article-title":"Building compact recognizer with recognition rate maintained for on-line handwritten Japanese text recognition","volume":"35","author":"Gao","year":"2014","journal-title":"Pattern Recognition Letters"},{"issue":"5","key":"10.3233\/JIFS-201613_ref5","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1016\/j.patrec.2012.12.005","article-title":"Effect of delayed strokes on the recognition of online Farsi handwriting","volume":"34","author":"Ghods","year":"2013","journal-title":"Pattern Recognition Letters"},{"issue":"4","key":"10.3233\/JIFS-201613_ref6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1142\/S0218001413530029","article-title":"An Efficient Post-Processing Algorithm for Online Handwritten Gurmukhi Character Recognition Using Set Theory","volume":"27","author":"Kumar","year":"2013","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"},{"key":"10.3233\/JIFS-201613_ref9","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1016\/j.patcog.2004.02.003","article-title":"Indian script character recognition: a survey","volume":"37","author":"Pal","year":"2004","journal-title":"Journal of Pattern Recognition"},{"issue":"1","key":"10.3233\/JIFS-201613_ref11","first-page":"81","article-title":"Fusion of Complementary online and offline strategies for recognition of handwritten Kannada characters","volume":"17","author":"Rampalli","year":"2011","journal-title":"Universal Computer Science"},{"issue":"4","key":"10.3233\/JIFS-201613_ref12","first-page":"2534","article-title":"Stroke-Database design for online handwriting recognition in Bangla","volume":"2","author":"Roy","year":"2012","journal-title":"International Journal of Modern Engineering Research"},{"issue":"4","key":"10.3233\/JIFS-201613_ref15","first-page":"439","article-title":"HMM based online handwritten Gurmukhi character recognition","volume":"9","author":"Sharma","year":"2010","journal-title":"Journal of Machine Graphics and vision"},{"issue":"3","key":"10.3233\/JIFS-201613_ref16","first-page":"52","article-title":"A framework of online handwritten Gurmukhi script recognition","volume":"6","author":"Singh","year":"2015","journal-title":"International Journal of Computer Science And Technology"},{"issue":"8","key":"10.3233\/JIFS-201613_ref18","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1109\/34.57669","article-title":"The State of the Art in online handwriting recognition","volume":"12","author":"Tappert","year":"1990","journal-title":"IEEE Transaction on Pattern Analysis and Machine Intelligence"},{"issue":"1","key":"10.3233\/JIFS-201613_ref19","first-page":"51","article-title":"Comparision of HMM-and SVM-based stroke classifiers for Gurmukhi script","volume":"28","author":"Verma","year":"2016","journal-title":"Neural Comput Appl"},{"issue":"8","key":"10.3233\/JIFS-201613_ref20","doi-asserted-by":"crossref","first-page":"3957","DOI":"10.1007\/s00521-017-3340-x","article-title":"Efficient zone identification approach for the recognition of online handwritten Gurmukhi script","volume":"31","author":"Singh","year":"2018","journal-title":"Neural Computing and Applications"},{"issue":"11","key":"10.3233\/JIFS-201613_ref21","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1007\/s12046-018-0961-4","article-title":"Recognition of online unconstrained handwritten Gurmukhi characters based on finite state automata","volume":"43","author":"Singh","year":"2018","journal-title":"S\u0101dhan\u0101"},{"key":"10.3233\/JIFS-201613_ref22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.inffus.2019.10.010","article-title":"Indic handwritten script identification using offline-online multi-modal deep network","volume":"57","author":"Bhunia","year":"2020","journal-title":"Inf Fusion"},{"issue":"2","key":"10.3233\/JIFS-201613_ref23","first-page":"1","article-title":"Fusion of spatio-temporal information for indic word recognition combining online and offline text data","volume":"19","author":"Mukherjee","year":"2019","journal-title":"ACM Trans Asian Low Resour Lang Inf Process (TALLIP)"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-201613","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:43:26Z","timestamp":1777455806000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-201613"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,2]]},"references-count":14,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/jifs-201613","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,3,2]]}}}