Comparing the Performance of Handwritten Number Recognition in Devanagari and Gurmukhi Script
DOI:
https://doi.org/10.32628/IJSRST52310636Keywords:
Handwritten Numeral Recognition, ANN, Feature Extraction, Grid Technique, Classification.Abstract
In this work, we compared the effectiveness of two distinct approaches for numerical recognition. This work aims to offer a dependable and effective technique for handwritten numeral recognition. The Image Centroid Zone feature extraction and recognition algorithm is used in the first method. This method involves extracting the image's features, which are then compared to the feature set of a database image for categorization. In contrast, the second approach uses Zone Centroid Zone methods to extract features, which are then used to train a support vector machine (SVM) to recognize the input image. The study field of Handwritten Optical Numeral Recognition (HONR) is significant due to its extensive applicability in various fields such as bank cheque reading, postcode reading, form processing, post offices and hospitals.
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