Analysis of Text Recognition with Data Mining Techniques

Bindushree V.¹ , Rashmi G.R.² , Uma H.R.³

Section:Review Paper, Product Type: Journal-Paper
Vol.7 , Issue.6 , pp.40-42, Dec-2019

Online published on Dec 31, 2019

Copyright © Bindushree V., Rashmi G.R., Uma H.R. . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Recognization of text is a method that recognizes text from the file in the desired format (such as .doc or.txt).This process involves several steps, including pre-processing, segmentation, feature extraction, classification, and post-processing. The pre-processing is performed as a binarized image to convert a gray scale image, and noise is reduced on the input image of the basic operation performed by removing the noise of the image signal. The segmentation phase is used to segment the image given online and segment each character of the segmentation line. Feature extraction is to compute the characteristics of the image document. This document describes techniques for converting the textual content of a paper document into a machine-readable format. This paper analyzes and compares the technical challenges, methods, and performance of text detection and recognition studies in colour images.

Key-Words / Index Term :
Feature Extraction, Recognition

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