CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

A New Morphology-based Method for Text Detection in Image and Video

by Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 13
Year of Publication: 2014
Authors: Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour
10.5120/18131-9251

Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour . A New Morphology-based Method for Text Detection in Image and Video. International Journal of Computer Applications. 103, 13 ( October 2014), 1-5. DOI=10.5120/18131-9251

@article{ 10.5120/18131-9251,
author = { Zaynab El Khattabi, Youness Tabii, Abdelhamid Benkaddour },
title = { A New Morphology-based Method for Text Detection in Image and Video },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 13 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number13/18131-9251/ },
doi = { 10.5120/18131-9251 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:25.789093+05:30
%A Zaynab El Khattabi
%A Youness Tabii
%A Abdelhamid Benkaddour
%T A New Morphology-based Method for Text Detection in Image and Video
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 13
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Text supply crucial suggestions for understanding video content, also the information that the text convey is much more concise than corresponding audio or video. The reason is that we need language knowledge to understand the text, and the knowledge itself does not need to be embedded in the text data. Text streams contain very rich semantic information. How to effectively extract information from text is an important component in video content analysis and semantics research. In this paper, a new morphology-based method for text detection in image and video is proposed. It consists of three major stages. In the first stage, the input color image is converted to gray-scale, a morphological binary map is generated by calculating the difference between the closing image and the opening image, and a binarization is performed. In the second stage, candidate regions are connected by using a morphological dilation and erosion operations. In the last stage, the extracted regions are verified based on characteristic of text regions to eliminate non text regions.

References
  1. S. A. Angadi and M. M. Kodabagi. A texture based methodology for text region extraction from low resolution natural scene images. In Advance Computing Conference (IACC), 2010 IEEE 2nd International, 19-20 February 2010.
  2. M. Anthimopoulos, B. Gatos, and I. Pratikakis. A two-stage scheme for text detection in video images. Image and Vision Computing, Volume 28, September 2010.
  3. M. S. Das, B. H. Bindhu, and A. Govardhan. Evaluation of text detection and localization methods in natural images. International Journal of Emerging Technology and Advanced Engineering, Volume 2, June 2012.
  4. S. Escalera, X. Bar´o, J. Vitri`a, and P. Radeva. Text detection in urban scenes. In Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence, 2009.
  5. Partha Sarathi Giri. Text information extraction and analysis from images using digital image processing techniques. Special Issue of International Journal on Advanced Computer Theory and Engineering (IJACTE), Volume 2, 2013.
  6. K. Jung, K. I. Kim, and A. K. Jain. Text information extraction in images and video: a survey. Pattern Recognition, Volume 37, May 2004.
  7. Lukas Neumann. Scene text recognition in images and video. 31 August 2012.
  8. Y. F Pan, X. Hou, and C. L Liu. Text localization in natural scene images based on conditional random field. In 10th International Conference on Document Analysis and Recognition, 2009. ICDAR '09, 26-29 July 2009.
  9. P. Patel and S. Tiwari. Text segmentation from images. International Journal of Computer Applications (0975 8887), Volume 67(19), April 2013.
  10. T. Pratheeba, V. Kavitha, and S. R. Rajeswari. Morphology based text detection and extraction from complex video scene. International Journal of Engineering and Technology, Volume 2, 2010.
  11. V. V. Rampurkar, G. J. Chhajed, and S. K. Shah. Review on text string detection from natural scenes. International Journal of Engineering and Innovative Technology (IJEIT), October 2012.
  12. L. SeongHun, J. H Seok, M. KyungMin, and K. JinHyung. Scene text extraction using image intensity and color information. In Chinese Conference on Pattern Recognition CCPR 2009, 4-6 November 2009.
  13. Y. Zhong, Z. Hongjiang, A. K. Jain, and Fellow. Automatic caption localization in compressed video. IEEE Transactions on pattern analysis and machine intelligence, Volume 22(4), April 2000.
  14. M. K. Y. W. K. Zhu and Q. Feihu. Using adaboost to detect and segment characters from natural scenes. In Proceedings of First Camera-based Document Analysis and Recognition, 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Information retrieval Text detection Morphology Text recongnition

Powered by PhDFocusTM