Abstract
Medical diagnostics today is based mainly on invasive methods and it should be strongly emphasised that they include not only the X-ray imaging, but also CT and MRI scanning. For several years in various research centres, there have been attempts to create a non-invasive medical diagnostic systems based on the fusion of photogrammetric and computer vision methods. Both the complexity of the problem and commitment to used well-known methods of diagnosis in medical circles did not allow for the creation of a fully functional prototype of system that could be implemented. In the paper, the authors present the problem of 3D reconstruction with a diagnosis of suitability of various matching methods used for rectified images. The result clearly indicate the superiority of the algorithm based on variational solution. The authors in their work on the development of photogrammetric non-invasive medical diagnostic system have not come across such an analysis. Therefore, they concluded that presenting such an analysis will be useful in further research.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Daniilidis, K., Klette, R.: Imaging Beyond the Pinhole Camera”, Computational Imaging and Vision, vol. 33. Springer (2006)
D’apuzzo, N.: Automated Photogrammetric Measurement of Human Faces. In: Int. Archives of Photogrammetry and Remote Sensing, Hakodate, Japan, vol. XXXII, Part B5, pp. 402–407 (1998)
D’apuzzo, N.: Measurement and modelling of human faces from multi images. International Archives of Photogrammetry and Remote Sensing 34(5), 241–246 (2002)
Bailey, D., Borwein, J., Mattingly, A., Wightwick, G.: The Computation of Previously Inaccessible Digits of and Catalan’s Constant, Notices of the American Mathematical Society (2011), http://crd.lbl.gov/~dhbailey/dhbpapers/bbp-bluegene.pdf (accessed April 15, 2011)
Berggren, L., Borwein, J.M., Borwein, P.B.: Pi: a Source Book. Springer, New York (2004)
Bouguet, J-Y.: Camera calibration toolbox for Matlab, http://www.vision.caltech.edu/bouguetj/calib_doc/index.html
Brown, D.C.: Decentering Distortion of Lenses. Photometric Engineering 32, 444–462 (1966)
Brown, D.C.: Close-range camera calibration. Photogrammetric Engineering 37, 855–866 (1971)
Chang, Y.: A Photogrammetric System for 3D Reconstruction of a Scoliotic Torso, A Master Thesis, Department of Geomatics Engineering, University of Calgary, Canada (2008)
Cyganek, B., Siebert, J.: An Introduction to 3D Computer Vision Techniques and Algorithms. Willey (2009)
Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM 24, 381–395 (1981)
Forsyth, D., Ponce, J.: Computer Vision: A Modern Approach. Prentice-Hall (2003)
Fryer, J.G., Brown, D.C.: Lens distortion for close-range photogrammetry. Photogrammetric Engineering and Remote Sensing 52, 51–58 (1986)
Harris, C., Stephens, M.: A combined corner and edge detector. In: Proceedings of Alvey Vision Conference, vol. 15, pp. 147–151 (1988)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press (2006)
Heikkila, J., Silven, O.: A four-step camera calibration procedure with implicit image correction. In: Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition, p. 1106 (1997)
Hirschmuller, H.: Stereo Processing by Semiglobal Matching and Mutual Information. IEEE Transactions on Pattern Analysis and Machine Intelligence 30 (2008)
Konolige, K.: Small vision system: Hardware and implementation. In: Proceedings of the International Symposium on Robotics Research, Hayama, Japan, pp. 111–116 (1997)
Korzynska, A., Iwanowski, M.: Multistage morphological segmentation of brightfield and fluorescent microscopy images. Opto-Electronics Review 20(2), 174–186 (2012)
Korzynska, A., Hoppe, A., Strojny, W., et al.: Investigation of a combined texture and contour method for segmentation of light microscopy cell images. In: Proceedings of the Second IASTED International Conference on Biomedical Engineering 2004, pp. 234–239 (2004)
Kosov, S., Thormählen, T., Seidel, H.-P.: Accurate Real-Time Disparity Estimation with Variational Methods. In: 5th International Symposium on Visual Computing, USA (2009)
Kraus, K.: Photogrammetry. Walter de Gruyter, Berlin (2007)
Lewis, J.P.: Fast normalized cross-correlation. Vision Interface, 120–123 (1995)
Luong, Q.T., Faugeras, O.D.: The Fundamental Matrix: Theory, Algorithms, and Stability Analysis. International Journal of Computer Vision 17(1), 43–75 (1996)
Malian, A., Azizi, A., Van Den Heuvel, F.A.: Medphos: A new photogrammetric system for medical measurement. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 35(B5), 311–316 (2004)
Mitchell, H.L.: Applications of digital photogrammetry to medical investigations. ISPRS Journal of Photogrammetry and Remote Sensing 50(3), 27–36 (1995)
Mitchell, H.L., Newton, I.: Medical photogrammetric measurement: overview and prospects. ISPRS Journal of Photogrammetry and Remote Sensing 56(5-6), 286–294 (2002)
Noble, A.: Descriptions of Image Surfaces, PhD thesis, Department of Engineering Science, Oxford University (1989)
Patias, P.: Medical imaging challenges photogrammetry. ISPRS Journal of Photogrammetry and Remote Sensing 56(5-6), 295–310 (2002)
Popielski, P., Wróbel, Z.: The feature detection on the homogeneous surfaces with projected pattern. In: Piętka, E., Kawa, J. (eds.) ITIB 2012. LNCS, vol. 7339, pp. 118–128. Springer, Heidelberg (2012)
Porwik, P., Para, T.: Some handwritten signature parameters in biometric recognition process. In: Proceedings of the ITI 2007 29th International Conference on Information Technology Interfaces Book Series: ITI 2007, pp. 185–190 (2007)
Porwik, P., Wrobel, K., Doroz, R.: The Polish Coins Denomination Counting by Using Oriented Circular Hough Transform. In: Kurzynski, M., Wozniak, M. (eds.) Computer Recognition Systems 3. AISC, vol. 57, pp. 569–576. Springer, Heidelberg (2009)
Schenk, T.: Digital photogrammetry, TerraScience, Laurelville, Ohio, 428 (1999)
Shapiro, L., Stockman, G.C.: Computer Vision. Prentice-Hall (2002)
Wróbel, K., Doroz, R.: The new method of signature recognition based on least squares contour alignment. In: International Conference on Biometrics and Kansei Engineering, pp. 80–83 (2009)
Zhang, Z.: Flexible camera calibration by viewing a plane from unknown orientations. In: Proceedings of the 7th International Conference on Computer Vision, Corfu, pp. 666–673 (1999)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence 22, 1330–1334 (2000)
Kajan, E.: Information technology encyclopedia and acronyms. Springer, Heidelberg (2002)
Broy, M.: Software engineering – From auxiliary to key technologies. In: Broy, M., Denert, E. (eds.) Software Pioneers. Springer, Heidelberg (2002)
Che, M., Grellmann, W., Seidler, S.: Appl. Polym. Sci. 64, 1079–1090 (1997)
Ross, D.W.: Lysosomes and storage diseases. MA Thesis. Columbia University, New York (1977)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Popielski, P., Wrobel, Z., Koprowski, R. (2013). The Effectiveness of Matching Methods for Rectified Images. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_47
Download citation
DOI: https://doi.org/10.1007/978-3-319-00969-8_47
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00968-1
Online ISBN: 978-3-319-00969-8
eBook Packages: EngineeringEngineering (R0)