Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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An X-ray Image Panorama System Using Robust Feature Matching and Per ception-Based Image Enhancement

  • Wang, Weiwei (Computer Science & Computer Engineering, Chonbuk National University Computer Graphics Lab.) ;
  • Gwun, Oubong (Computer Science & Computer Engineering, Chonbuk National University Computer Graphics Lab.)
  • Received : 2011.09.14
  • Accepted : 2012.03.06
  • Published : 2012.05.31
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Abstract

This paper presents an x-ray medical image panorama system which can overcome the smallness of the images that exist on a source computer during remote medical processing. In the system, after the standard medical image format DICOM is converted to the PC standard image format, a MSR algorithm is used to enhance X-ray images of low quality. Then SURF and Multi-band blending are applied to generate a panoramic image. Also, this paper evaluates the proposed SURF based system through the average gray value error and image quality criterion with X-ray image data by comparing with a SIFT based system. The results show that the proposed system is superior to SIFT based system in image quality.

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References

  1. T. Makela, Dental X-ray Image Stitching Algorithm, Master's Thesis of Helsinki University of Technology, 2009.
  2. Y. Ma, "A New Method of Microscopic Images' Automatic Mosaicking," Bioinformatics and Biomedical Engineering, ICBBE 2009, pp. 1-5, 2009.
  3. J. Xu, "A Medical Image Mosaicking Technology Based on Venous Diagnosis," Biomedical Engineering and Computer Science, ICBECS2010, pp. 1-4, 2010.
  4. G. Lou and Y. Han, "Research on Processing and Analysis Method for Medical CT Image," 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering, pp. 97-100, 2010.
  5. Z. Rahman, "Multi-Scale Retinex for Color Image Enhancement," Image Processing, Vol.3 pp. 1003-1006, 1996.
  6. M. Brown and D.G. Lowe, "Automatic Panoramic Image Stitching using Invariant Features," International J ournal of Computer Vision, Vol.74, No.1, pp. 59-73, 2007. https://doi.org/10.1007/s11263-006-0002-3
  7. D.G. Lowe, "Distinctive Image Features from Scale Invariant Keypoints," International Journal of Computer Vision, Vol.60, No.2, pp. 91-110, 2004. https://doi.org/10.1023/B:VISI.0000029664.99615.94
  8. H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool, "SURF: Speeded Up Robust Features," Computer Vision and Image Understanding, Vol.110, No.3, pp. 346-359, 2008. https://doi.org/10.1016/j.cviu.2007.09.014
  9. G. Lou and Y. Han, "Research on Processing and Analysis Method for Medical CT Image," 2010 International Conference on Computer and Communication Technologies in Agriculture Engineering, pp. 97-100, 2010
  10. D.J. Jobson and Z. Rahman, "Properties and Performance of a Center/Surround Retinex," IEEE Trans. on Image Processing, Vol.6, No.3, pp. 451-462, 1997. https://doi.org/10.1109/83.557356
  11. J. Lou and O. Gwun, "A Comparison of SIFT, PCA-SIFT and SURF," International Journal of Image Processing, Vol.3, No.4, pp. 143-152, 2009.
  12. M.A. Fischler and R.C. Bolles, "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography," Comm. of the ACM, Vol.24, No. 6, pp. 381-395, 1981. https://doi.org/10.1145/358669.358692
  13. P.J. Burt and E.H. Adelson, "A Multiresolution Spline with Application to Image Mosaics," ACM Trans. On Graphics, Vol.2, No.4, pp. 217-236, 1983. https://doi.org/10.1145/245.247
  14. L. Juan, S. Shin, H. Park, and O. Gwun, "Stitching for Panorama Based on SURF and Multi-band Blending," Journal of Korea Multimedia Society, Vol.14, No.2, pp.201-209, 2011. https://doi.org/10.9717/kmms.2011.14.2.201