A Text Location Method for Web Images

Xin Ning; Wei Jun Li; Wen Jie Liu

doi:10.4028/www.scientific.net/AMR.926-930.3350

Paper Titles

Water Surface Floater Clustering Based on Mean Shift
p.3334

A Hybrid Particle Swarm Optimization Algorithm for Dynamic Environments
p.3338

A New Fast Algorithm for Intra Prediction Mode Selection in the High Efficiency Video Coding (HEVC) Standard
p.3342

A Satisfaction Differential Evolution Algorithm for Detailed Machine Layout in Assembly Plant
p.3346

A Text Location Method for Web Images
p.3350

An Ant Colony Algorithm with Memory Grouping List for Multi-Depot Vehicle Routing Problem
p.3354

An Innovative Game Method for Multilevel-Objective Optimization
p.3359

Algorithm Optimization of Shape Setup Calculation in Hot Strip Mill
p.3364

Bidirectional Maximal Matching Word Segmentation Algorithm with Rules
p.3368

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 926-930A Text Location Method for Web Images

A Text Location Method for Web Images

Abstract:

This paper proposes a text localization method with multi-features based on cascade classifier for a variety of web images. Specifically, first, the original image is divided into sub-images with different scales, which form more satisfactory edge image blocks after being pretreated respectively; then, the researchers determine in the classifier whether the text area is contained in the candidate image blocks according to the edge connectivity characteristics, stroke density characteristics and text arrangement characteristics of text area; finally, the location results of sub-images with different scales are mixed together to obtain the final result. The experiments show that this location method has the relatively high precision and recall rate and quite strong robustness, which is suitable for a variety of web images.

You might also be interested in these eBooks

Progress in Applied Sciences, Engineering and Technology

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 926-930)

Pages:

3350-3353

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.926-930.3350

Citation:

Cite this paper

Online since:

May 2014

Authors:

Xin Ning, Wei Jun Li*, Wen Jie Liu

Keywords:

Cascade Classifier, Edge Extraction, Feature Analysis, Text Location

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] B.L. Su, S.J. Lu and T.Q. Pan: Processings of 21st International Conference on Pattern Recognition (Tsukuba, 2012), p.3042.

Google Scholar

[2] C.C. Xiang, Y. Wen: Processings of 2011 International Conference on Document Analysis and Recognition (Kunming, 2011), p.218.

Google Scholar

[3] C. Su, X.D. Hu and B.F. Wang: Journal of Computer Applications, Vol. 32 (2012) No. 8, p.2305.

Google Scholar

[4] C. Li, X.Q. Ding and Y.S. Wu: Proceedings of 6th International Conference on Document Analysis and Recognition (Seattle, 2001), p.1069.

Google Scholar

[5] J. Y He, S.F. Li: Proceedings of the Third International Conference on Image and Graphics (Hong Kong, 2004), p.361.

Google Scholar

[6] J. Q Yan, D.C. Tao and C.N. Tian: Proceedings of 2010 IEEE International Conference on Systems Man and Cybernetics. Istanbul (Istanbul, 2010), p.3896.

Google Scholar

[7] Y. Deng, X.H. Wu and B.H. Yong: Computer Applications and Software, Vol. 29 (2012) No. 12, p.286.

Google Scholar

[8] J.F. Han, L.L. Song: Journal of Computer-Aided Design & Computer Graphics, Vol. 25 (2013) No. 1, p.62.

Google Scholar

[9] T. Y, M. M: Processings of the 17th International Conference on Pattern Recognition. Cambridge (Cambridge, 2004), p.687.

Google Scholar

[10] A. B Ayman, Q. Rami and L. Stan: Processings of IEEE International Conferenceon Signal Processing and Communications (Dubai, 2007), p.1283.

Google Scholar