Offline Handwritten MODI Character Recognition Using HU, Zernike Moments and Zoning
Sadanand A. Kulkarni, Prashant L. Borde, Ramesh R. Manza, Pravin L., Yannawar

TL;DR
This paper presents a method for recognizing handwritten MODI characters using Zernike moments and zoning, demonstrating the effectiveness of Zernike moments over Hu moments for shape description in an offline recognition system.
Contribution
The work introduces the use of Zernike moments combined with zoning for improved recognition of complex handwritten MODI characters, highlighting their rotation invariance and shape description capabilities.
Findings
Zernike moments outperform Hu moments in recognition accuracy.
Zoning enhances feature extraction for handwritten MODI characters.
The method achieves efficient offline recognition of complex scripts.
Abstract
HOCR is abbreviated as Handwritten Optical Character Recognition. HOCR is a process of recognition of different handwritten characters from a digital image of documents. Handwritten automatic character recognition has attracted many researchers all over the world to contribute handwritten character recognition domain. Shape identification and feature extraction is very important part of any character recognition system and success of method is highly dependent on selection of features. However feature extraction is the most important step in defining the shape of the character as precisely and as uniquely as possible. This is indeed the most important step and complex task as well and achieved success by using invariance property, irrespective of position and orientation. Zernike moments describes shape, identify rotation invariant due to its Orthogonality property. MODI is an ancient…
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Taxonomy
TopicsHandwritten Text Recognition Techniques · Image Retrieval and Classification Techniques · Image Processing and 3D Reconstruction
