Open AccessReview Paper on Various Methodology of Text Extraction from Image
Author(s) -
Rucha Patil,
Smruti Khati,
Tulsi Thakur,
Harshita Katragadda,
Neha Ambulkar,
Ketki Bhakare
Publication year - 2015
Publication title -
journal of advance research in computer science and enigneering
Language(s) - English
Resource type - Journals
ISSN - 2456-3552
DOI - 10.53555/nncse.v2i3.501
Subject(s) - computer science , character (mathematics) , artificial intelligence , skew , feature extraction , segmentation , optical character recognition , word (group theory) , pattern recognition (psychology) , domain (mathematical analysis) , image (mathematics) , artificial neural network , text segmentation , image segmentation , information extraction , support vector machine , noise (video) , natural language processing , mathematics , telecommunications , mathematical analysis , geometry
This review presents the various text extraction techniques and also compares the research results of various researchers in the domain of text extraction. A generic character recognition system has different stages like noise removal, skew detection and correction, segmentation, feature extraction and character recognition. Input is digitized image containing any text, which is preprocessed to segment it into normalized individual word and letters. The OCR, Neural Network, SVM are the various methods for text extraction. Text extraction helps to preserve history by making information efficiently searchable, easily manageable without the need for human labor.