Open AccessEfficient Technique for word identification and recognition in Telugu Documents
Author(s) -
K. Mohana Lakshmi,
Tummala Ranga Babu
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3793.078219
Subject(s) - telugu , artificial intelligence , computer science , natural language processing , scale invariant feature transform , codebook , word (group theory) , identification (biology) , bag of words model , devanagari , feature (linguistics) , bag of words model in computer vision , cluster analysis , support vector machine , speech recognition , visual word , pattern recognition (psychology) , feature extraction , mathematics , image (mathematics) , linguistics , image retrieval , character recognition , philosophy , botany , biology , geometry
Telugu language is one of the most spoken Indian languages throughout the world. Since it has an old heritage, so Telugu literature and newspaper publications can be scanned to identify individual words. Identification of Telugu word images poses serious problems owing to its complex structure and larger set of individual characters. This paper aims to develop a novel methodology to achieve the same using SIFT (Scale Invariant Feature Transform) features of telugu words and classifying these features using BoVW (bag of visual words). The features are clustered to create a dictionary using k-means clustering. These words are used to create a visual codebook of the word images and the classification is achieved through SVM (Support Vector Machine).