Base on SIFT-Harris Operator of the Document Image Matching Method

Yuan Hang Cheng; Xiao Wei Han

doi:10.4028/www.scientific.net/AMR.524-527.3870

Paper Titles

Design and Realization Based on SAR Image Target Model Base
p.3849

Research on Construction of the Mutually Supportive Network Using a Spring-Water Spots
p.3853

Study of Teaching Assessment Based on BP Neural Network
p.3861

Text Classification Combined an Improved CHI and Category Relevance Factor
p.3866

Base on SIFT-Harris Operator of the Document Image Matching Method
p.3870

Analysis of the Development of Contemporary Industrial Design
p.3875

Study of Application of “Green” Design Concept to Fashion Design
p.3880

Weighted-Correct Empirical likelihood for Linear EV Models
p.3884

Integrated Evaluation of Ship Maneuverability Based on the Method of Maximizing Deviation
p.3888

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 524-527Base on SIFT-Harris Operator of the Document Image...

Base on SIFT-Harris Operator of the Document Image Matching Method

Abstract:

Abstract：Proposed a method of document image matching based on SIFT-Harris operator, Use of SIFT-Harris operator to accurately search match for the same name point. First use SIFT operator for the coarse search match to find out a rough affine transformation relationship of matched Image and based image, Then used the Harris operator and gray correlation matching algorithm refined search. It improved the matching speed and accuracy. Experimental results show that the method works well for document image matching.

You might also be interested in these eBooks

Natural Resources and Sustainable Development II

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 524-527)

Pages:

3870-3874

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.524-527.3870

Citation:

Cite this paper

Online since:

May 2012

Authors:

Yuan Hang Cheng, Xiao Wei Han

Keywords:

Document Image, Match, SIFT-Harris

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] S. Gold and A. Rangarajan. A graduated assignment algorithm for graph matching. IEEE Trans. PAMI, 18(4):377–388, April 2009.

DOI: 10.1109/34.491619

Google Scholar

[2] F. Isgr`o and M. Pilu. A fast and robust image registration method based on an early consensus paradigm. Pattern Recognition Letters, 25(8): 943 – 954, 2006.

DOI: 10.1016/j.patrec.2004.02.010

Google Scholar

[3] Y. Ke and R. Sukthankar. PCA-SIFT: a more distinctive representation for local image descriptors . In Proc. CVPR, volume 2, pages 506–513, 2006.

DOI: 10.1109/cvpr.2004.1315206

Google Scholar

[4] J. Liang, D. DeMenthon, and D. Doermann. Flattening curved documents in images. In Proc. CVPR, pages 338–345, 2009.

DOI: 10.1109/cvpr.2005.163

Google Scholar

[5] M. Mirmehdi, P. Clark, and J. Lam. Extracting low resolution text with an active camera for OCR. In Proc. IX Spanish Sym. Pat. Rec. and Image Proc., pages 43–48, May 2001.

Google Scholar

[6] T. Nakao, A. Kashitani, and A. Kaneyoshi. Scanning a document with a small camera attached to a mouse. In Proc. WACV'98, pages 63–68, 1998.

DOI: 10.1109/acv.1998.732859

Google Scholar

[7] B. S. Reddy and B. N. Chatterji. An FFT-based technique for translation, rotation, and scale- invariant image registration. IEEE Trans. Image Proc., 5(8):1266–1271, 2006.

DOI: 10.1109/83.506761

Google Scholar

[8] K. Schutte and A. M. Vossepoel. Accurate mosaicking of scanned maps, or how to generate a virtual a0 scanner. In Proc. ASCI'95, pages 353–359, 2005.

Google Scholar

[9] A. P. Whichello and H. Yan. Document image mosaicing. In Proc. ICPR, pages 1081–1083, 2008.

Google Scholar

[10] A. Zappala, A. Gee, and M. J. Taylor. Document mosaicing. Image and Vision Computing, 17(8):585–595, 2009.

Google Scholar