A Single Euler Number Feature for Multi-font Multi-size Kannada Numeral Recognition

Multi-font Multi-size Kannada Numeral Recognition Based on Structural Features

In this paper a fast and novel method is proposed for multi-font multi-size Kannada numeral recognition which is thinning free and without size normalization approach. The different structural feature are used for numeral recognition namely, directional density of pixels in four directions, water reservoirs, maximum profile distances, and fill hole density are used for the recognition of Kannada numerals. A Euclidian minimum distance criterion is used to find minimum distances and K-nearest neighbor classifier is used to classify the Kannada numerals by varying the size of numeral image from 1…

Spatial Features for Multi-Font/Multi-Size Kannada Numerals and Vowels Recognition

This paper presents multi-font/multi-size Kannada numerals and vowels recognition based on spatial features. Directional spatial features viz stroke density, stroke length and the number of stokes in an image are employed as potential features to characterize the printed Kannada numerals and vowels. Based on these features 1100 numerals and 1400 vowels are classified with Multi-class Support Vector Machines (SVM). The proposed system achieves the recognition accuracy as 98.45% and 90.64% for numerals and vowels respectively.

Classifier Fusion Method to Recognize Handwritten Kannada Numerals

Optical Character Recognition (OCR) is one of the important fields in image processing and pattern recognition domain. Handwritten character recognition has always been a challenging task. Only a little work can be traced towards the recognition of handwritten characters for the south Indian languages. Kannada is one such south Indian language which is also one of the official language of India. Accurate recognition of Kannada characters is a challenging task because of the high degree of similarity between the characters. Hence, good quality features are to be extracted and better classifiers…

Lipi Gnani - A Versatile OCR for Documents in any Language Printed in Kannada Script

A Kannada OCR, named Lipi Gnani, has been designed and developed from scratch, with the motivation of it being able to convert printed text or poetry in Kannada script, without any restriction on vocabulary. The training and test sets have been collected from over 35 books published between the period 1970 to 2002, and this includes books written in Halegannada and pages containing Sanskrit slokas written in Kannada script. The coverage of the OCR is nearly complete in the sense that it recognizes all the punctuation marks, special symbols, Indo-Arabic and Kannada numerals and also the intersp…

Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classification

In this paper, we propose a Seed-Augment-Train/Transfer (SAT) framework that contains a synthetic seed image dataset generation procedure for languages with different numeral systems using freely available open font file datasets. This seed dataset of images is then augmented to create a purely synthetic training dataset, which is in turn used to train a deep neural network and test on held-out real world handwritten digits dataset spanning five Indic scripts, Kannada, Tamil, Gujarati, Malayalam, and Devanagari. We showcase the efficacy of this approach both qualitatively, by training a Bounda…

多语言视频字幕数据集：面向基于图像的文字识别

Multi-language Video Subtitle Dataset for Image-based Text Recognition

该研究构建了一个包含4,224张多语言字幕图像的数据集，涵盖157种字符，旨在支持复杂背景下多语言文字识别及深度学习模型的开发与评估。