On-line handwritten character recognition system for Kannada using Principal Component Analysis Approach: For handheld devices

Abstract

In this paper, we present an unrestricted Kannada online handwritten character recognizer which is viable for real time applications. It handles all basic characters of the Kannada script. In this paper, the proposed Online Handwritten Kannada Character Recognition System (OHKCRS) is discussed in detail. Developing an Online Handwriting Recognition System for Kannada character set to mobile devices would play an important role in making these devices available and usable for the Indian society as Kannada language is spoken in major part of India. In this paper, we present a model for writer-independent online handwriting character recognition for the 51 basic Kannada characters. The proposed system is implemented on mobile device using two different approaches namely Principal Component Analysis (PCA) and Dynamic Time Wrapping (DTW). To find the suitability of these two approaches for handheld devices several experiments were conducted and detailed analysis has been made on the obtained results. The results obtained for PCA approach is quite promising than DTW. On an average, recognition accuracy up to 88% is achieved for the PCA approach and up to 64% is achieved for DTW approach, also the time taken for recognition of unknown character is around 0.8 sec for PCA approach, and around 55 sec for DTW approach, thus the PCA approach is suitable for real-time applications.

Online Handwritten Text Recognition for Indian Scripts

“…Online HCR system for Kannada using Principal Component Analysis Approach is proposed by Parsad et al [45]. System is implemented on mobile device using two different approaches namely Principal Component Analysis (PCA) and Dynamic Time Wrapping (DTW), an average recognition accuracy of 88% for the PCA and up to 64% is achieved for DTW approach.…”