International Journal of Contents

The Korea Contents Association (한국콘텐츠학회)
권호 표지
DOI QR코드

DOI QR Code

Rectification of Perspective Text Images on Rectangular Planes

  • Le, Huy Phat (Department of Electronics and Computer Engineering Chonnam National University) ;
  • Madhubalan, Kavitha (Department of Electronics and Computer Engineering Chonnam National University) ;
  • Lee, Guee-Sang (Department of Electronics and Computer Engineering Chonnam National University)
  • Received : 2010.08.20
  • Accepted : 2010.12.07
  • Published : 2010.12.28
Download PDF
⟨ Previous Next ⟩

Abstract

Natural images often contain useful information about the scene such as text or company logos placed on a rectangular shaped plane. The 2D images captured from such objects by a camera are often distorted, because of the effects of the perspective projection camera model. This distortion makes the acquisition of the text information difficult. In this study, we detect the rectangular object on which the text is written, then the image is restored by removing the perspective distortion. The Hough transform is used to detect the boundary lines of the rectangular object and a bilinear transformation is applied to restore the original image.

Keywords

References

  1. G.K. Myers, R.C. Bolles, Quang-Tuan Luong, James A.Herson and Hrishikesh B. Aradhye, "Rectification and Recognition of Text in 3-D Scenes," International Journal on Document Analysis and Recognition, vol.7, no.2, 2004, pp. 147-158.
  2. C.R. Dance, "Perspective Estimation for Document Images," proceedings of the SPIE Conference on Document Recognition and Retrieval IX, 2002, pp. 244-254.
  3. S.J. Lu, B.M. Chen, C.C. Ko, "Perspective Rectification of Document Images Using Fuzzy Set and Morphological Operations," Imnage and Vision Computing, vol.23, 2005, pp.541-553. https://doi.org/10.1016/j.imavis.2005.01.003
  4. Lin Liu, “Slant Correction of Vehicle License Plate Image,” International Conference on Computer Science and Software Engineering, vol.3617, 2008, pp. 237-244.
  5. D.H. Han, H.K. Sung, K.T. Park, Y.H. Cho and H.M. Choi, “Neural network approach to the nonlinear shape restorations”, IEEE International Conference on Systems, Man, and Cybernetics, vol.1, 1996, pp.504-509. https://doi.org/10.1109/ICSMC.1996.569843
  6. Y.Y. Tang and C.Y. Suen, “Image transformation approach to nonlinear shape restoration,” IEEE Trans. Syst. Man Cybernet, Jan. 1993, pp. 155–171. https://doi.org/10.1109/21.214774
  7. Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, 2nd Edition, Prentice Hall, 1999.
  8. Huaigu Cao; Xiaoqing Ding; Changsong Liu; , "A image,” Ninth IEEE International Conference on Computer Vision, vol.1, 2003, pp.228-233.
  9. A. Criminisi, A. Zisserman, “Shape from texture: homogeneity revisited,” In Proc.11th British Machine Vision Conference, 2000, pp. 82–91.
  10. C. Rother, “A new approach for vanishing point detection in architectural environments,” In Proc.11th British Machine Vision Conference, 2000, pp. 382–391.
  11. Paul Clark, Majid Mirmehdi, “Rectifying perspective views of text in 3D scenes using vanishing points,” Pattern Recognition, vol.36, no.11, Nov. 2003, pp.2673-2686. https://doi.org/10.1016/S0031-3203(03)00132-8
  12. Li, T.D. Bui, C.Y. Suen, Y.Y. Tang and Q.L. Gu, “Splitting-integrating method for normalizing images by inverse transformations,” IEEE Trans on Pattern Anal. Mach. Intell, vol.14, no.6, 1992, pp. 678–686. https://doi.org/10.1109/34.141558
  13. R. Duda and P. Hart, “Use of the Hough transform to detect lines and curves in pictures,” Communications of the ACM, 1972, vol.15, No.1, pp.11–15.

Cited by

  1. Vanishing Points Detection in Indoor Scene Using Line Segment Classification vol.13, pp.8, 2013, https://doi.org/10.5392/JKCA.2013.13.08.001