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Reseach Article

Writer based Handwritten Document Image Retrieval

Published on April 2015 by Vijayalaxmi.m.b, B.v.dhandra
National conference on Digital Image and Signal Processing
Foundation of Computer Science USA
DISP2015 - Number 2
April 2015
Authors: Vijayalaxmi.m.b, B.v.dhandra
69be1339-3b0a-48e6-b52f-d5be3d8946cd

Vijayalaxmi.m.b, B.v.dhandra . Writer based Handwritten Document Image Retrieval. National conference on Digital Image and Signal Processing. DISP2015, 2 (April 2015), 30-34.

@article{
author = { Vijayalaxmi.m.b, B.v.dhandra },
title = { Writer based Handwritten Document Image Retrieval },
journal = { National conference on Digital Image and Signal Processing },
issue_date = { April 2015 },
volume = { DISP2015 },
number = { 2 },
month = { April },
year = { 2015 },
issn = 0975-8887,
pages = { 30-34 },
numpages = 5,
url = { /proceedings/disp2015/number2/20487-3019/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National conference on Digital Image and Signal Processing
%A Vijayalaxmi.m.b
%A B.v.dhandra
%T Writer based Handwritten Document Image Retrieval
%J National conference on Digital Image and Signal Processing
%@ 0975-8887
%V DISP2015
%N 2
%P 30-34
%D 2015
%I International Journal of Computer Applications
Abstract

In this paper a method is proposed for retrieval of handwritten document images based on the writer's handwriting using texture features of input handwritten document image block. Typically it can be observed that the patterns of any handwritten text blocks encompass spatial texture primitives. The conventional two-dimensional (2-D) discrete wavelet transforms (DWTs) and Correlation of GLCM is used to extract spatial features. Handwritten documents are collected from 100 writers each in English, Kannada and Hindi scripts. These handwritten documents are segmented into image blocks and 2000 image blocks of each script writers are used separately for validation of the proposed method. The similarity measures viz. , Euclidean and City block distances are used and achieved Top-1 retrieval rates as 100% for each of the Kannada, English and Hindi writers' document image blocks.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Texture Discrete Wavelet Transform Correlation Of Glcm Document Similarity Measurement Handwritten Documents Document Retrieval Writer Identification.