Call for Paper - October 2019 Edition
IJCA solicits original research papers for the October 2019 Edition. Last date of manuscript submission is September 20, 2019. Read More

Writer based Handwritten Document Image Retrieval

Print
PDF
IJCA Proceedings on National conference on Digital Image and Signal Processing
© 2015 by IJCA Journal
DISP 2015 - Number 2
Year of Publication: 2015
Authors:
Vijayalaxmi. M. B
B. V. Dhandra

Vijayalaxmi.m.b and B.v.dhandra. Article: Writer based Handwritten Document Image Retrieval. IJCA Proceedings on National conference on Digital Image and Signal Processing DISP 2015(2):30-34, April 2015. Full text available. BibTeX

@article{key:article,
	author = {Vijayalaxmi.m.b and B.v.dhandra},
	title = {Article: Writer based Handwritten Document Image Retrieval},
	journal = {IJCA Proceedings on National conference on Digital Image and Signal Processing},
	year = {2015},
	volume = {DISP 2015},
	number = {2},
	pages = {30-34},
	month = {April},
	note = {Full text available}
}

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

  • G. Pirlo , M. Chimienti, M. Dassisti, D. Impedovo, A. Galiano, A Layout-Analysis Based System for Document Image Retrieval, Mondo Digitale, Feb 2014.
  • M. S. Shirdhonkar and Manesh B. Kokare, "Handwritten Document Image Retrieval", International Journal of Modeling and Optimization, Vol. 2, No. 6, 2012, pp. 693-696 .
  • Adebayo Daramola, Ademola Abdulkareem, K. Joshua Adinfona, "Efficient Item Image Retrieval System", International Journal of Soft Computing and Engineering (IJSCE), ISSN: 2231-2307, Vol. 4, Issue-2, May 2014.
  • Vlad Atanasiu, Laurence Likforman-Sulem, Nicole Vincent, "Writer Retrieval—Exploration of a Novel Biometric Scenario Using Perceptual Features Derived from Script Orientation", Proc. 11th Intl. Conf. on Document Analysis and Recognition, Beijing, China, September 18–21, 2011 © IEEE.
  • Ralph Niels, Franc Grootjen, and Louis Vuurpijl, "Writer Identification through Information Retrieval: The AllographWeight Vector", Proc. 11th Intl. Conf. on Frontiers in Handwriting Recognition, Montreal, 2008.
  • Stefan Fiel and Robert Sablatnig, "Writer Retrieval and Writer Identification using Local Features", DAS, IEEE 2012, pp. 145-149.
  • Stefan Fiel and Robert Sablatnig, "Writer Identification and Writer Retrieval Using the Fisher Vector on Visual Vocabularies", 12th International Conference on Document Analysis and Recognition (ICDAR), IEEE, 2013, pp. 545 - 549.
  • Chawki Djeddi, Imran Siddiqi, Labiba Souici-Meslati, and Abdellatif Ennaji, "Multi-script Writer Identification Optimized with Retrieval Mechanism", ICFHR, pp. 509-514. 2012.
  • Ajinkya P. Nilawar, Image Retrieval Using Gradient operators, IJIRTCC, Volume: 2 Issue: 1, pp. 1-4, ISSN: 2321 -8169, Jan. 2014.
  • Rajiv Jain, Douglas W. Oard, and David Doermann, Scalable Ranked Retrieval Using Document Images, Document Recognition and Retrieval XXI, SPIE-IS&T/Vol. 9021, 90210K-1-90210K-15.
  • B. V. Dhandra, Vijayalaxmi. M. B, "Text and Script Independent Writer Identification", International Conference on Contemporary Computing and Informatics, Mysore, Nov. 27-29, 2014.
  • B. V. Dhandra, Vijayalaxmi. M. B, "Text Independent Writer Identification for Tamil Script", National conference on Advances in Modern Computing and Application Trends, AIT, Bangalore, 5-6 Dec 2014.
  • U. Marti and H. Bunke. The IAM-database: An English Sentence Database for Off-line Handwriting Recognition. Int'l Journal on Document Analysis and Recognition, Volume 5, pages 39 - 46, 2002.