Modeling of palm leaf character recognition system using transform based techniques

• Palm leaf character recognition is important as they contain literature, etc.
• The third dimension “Z” is the depth of indentation at each pixel point computed.
• The depth measured is in 100 of microns.
• Thereby “X, Y and Z” values are computed at each pixel point of Telugu character.
• Using these coordinate values patterns are generated in XY, YZ and XZ planes.

Optical character recognition (OCR) has been a well-known area of research for last five decades. This is an important application of pattern recognition in image processing. Automatic mail sorting generated interest in the handwritten character recognition (HCR) over a period of time. Palm leaf manuscripts which are very fragile and susceptible to damage caused by insects, contain huge amount of information relating to music, astrology, astronomy etc. Hence it becomes necessary for these manuscripts digitized and stored. These palm leaf manuscripts created interest for the young generation researchers since the last decade. This work exploits a special 3D feature (depth of indentation) which is proportional to the pressure applied by the scriber at that point. This 3D feature is obtained at each of the pixel point of a Telugu palm leaf character. In this work two dimensional Discrete wavelet transform (2-D DWT), two dimensional fast Fourier transform (2-D FFT) and two dimensional discrete cosine transform (2-D DCT) are used for feature extraction. The 3D feature along with the proposed two level transform based technique helps to obtain better recognition accuracy. The best recognition accuracy obtained in this model is 96.4%.