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Survey Paper | Computer Science & Engineering | India | Volume 3 Issue 3, March 2014 | Rating: 6.7 / 10
Writer Adaptation for Handwriting Recognition in Hindi Language - A Survey
Nupur Gulalkari, Shreya Prabhu, Anjali Pachpute, Rekha Sugandhi, Kapil Mehrotra
Abstract: With the advancement in technology, there is an increased use of pen-based touch screen devices and PDAs. These devices come with an alternative for the traditional alphanumeric or QWERTY keyboard which is input in the form of users handwriting. The handwriting is then converted into normal text form. However, these devices require prior training to be done by the user. There is a high demand for robust and accurate recognition systems in the practical applications of handwriting recognition. The real challenge lies with the selection of a classifier which gives accurate results in real-time, while making the system self-adaptive simultaneously. Thus, in this paper various classifiers have been studied so as to find the most appropriate classifier for anonline handwriting recognition system for handwriting in Hindi language that provides a way by which the touch screen device adapts itself to its user handwriting without prior training is studied.
Keywords: Active-DTW, Markov Model, Self -adaptation, SVM, Writer adaptation
Edition: Volume 3 Issue 3, March 2014,
Pages: 718 - 721