Title :
Online Handwriting Recognition of Tamil Script Using Fractal Geometry
Author :
Kunwar, Rituraj ; Ramakrishnan, A.G.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Sci. (IISc), Bangalore, India
Abstract :
We present a fractal coding method to recognize online handwritten Tamil characters and propose a novel technique to increase the efficiency in terms of time while coding and decoding. This technique exploits the redundancy in data, thereby achieving better compression and usage of lesser memory. It also reduces the encoding time and causes little distortion during reconstruction. Experiments have been conducted to use these fractal codes to classify the online handwritten Tamil characters from the IWFHR 2006 competition dataset. In one approach, we use fractal coding and decoding process. A recognition accuracy of 90% has been achieved by using DTW for distortion evaluation during classification and encoding processes as compared to 78% using nearest neighbor classifier. In other experiments, we use the fractal code, fractal dimensions and features derived from fractal codes as features in separate classifiers. While the fractal code is successful as a feature, the other two features are not able to capture the wide within-class variations.
Keywords :
data compression; handwriting recognition; handwritten character recognition; image classification; image coding; image matching; image reconstruction; DTW; Tamil script; character classification; character compression; character reconstruction; data redundancy; dynamic time warping; fractal coding method; fractal decoding; fractal geometry; nearest neighbor classifier; online handwriting recognition; online handwritten Tamil character recognition; Accuracy; Character recognition; Encoding; Fractals; Handwriting recognition; Image coding; Image reconstruction; Fractal coding; Fractal geometry; Online handwriting recognition; Online handwritten character recognition; Tamil character recognition; Tamil handwriting recognition;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.279