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Application of the Moment Shape Representations to the General Shape Analysis

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EN
Abstrakty
EN
The General Shape Analysis (GSA) is a task similar to the shape recognition and retrieval. However, in GSA an object usually does not belong to a template class, but can only be similar to some of them. Moreover, the number of applied templates is limited. Usually, ten most general shapes are used. Hence, the GSA consists in searching for the most universal information about them. This is useful when some general information has to be concluded, e.g. in coarse classification. In this paper the result of the application of three shape descriptors based on the moment theory to the GSA is presented. For this purpose the Moment Invariants, Contour Sequence Moments, and Zernike Moments were selected.
Twórcy
  • West Pomeranian University of Technology, Szczecin, Zolnierska 52, 71-210, Szczecin, Poland
Bibliografia
  • [1] Bator, M., Chmielewski, L.J. (2009). Finding regions of interest for cancerous masses enhanced by elimination of linear structures and considerations on detection correctness measures in mammography. Pattern Analysis and Applications, 12(4), 377–390
  • [2] Hu, M.K. (1962). Visual Pattern Recognition by Moment Invariants. IEEE Transactions on Information Theory, 8, 179–187
  • [3] Hupkens, Th.M., Clippeleir, J. de (1995). Noise and Intensity Invariant Moments. Pattern Recognition Letters, 16 (4), 371–376
  • [4] Khan, M.S., Coenen, F., Dixon, C., El-Salhi, S. (2012). A Classification Based Approach for Predicting Springback in Sheet Metal Forming. Journal of Theoretical and Applied Computer Science 6(2), 45–59
  • [5] Forczmanski P., Frejlichowski D. (2010). Robust Stamps Detection and Classification by Means of General Shape Analysis. Lecture Notes in Computer Science, 6374, 360–367
  • [6] Frejlichowski, D. (2010). An Experimental Comparison of Seven Shape Descriptors in the General Shape Analysis Problem. Lecture Notes in Computer Science, 6111, 294–305
  • [7] Frejlichowski, D. (2011). The Application of the Zernike Moments to the Problem of General Shape Analysis. Control and Cybernetics, 40(2), 515–526
  • [8] Frejlichowski, D., Forczmanski, P. (2010). General Shape Analysis Applied to Stamps Retrieval from Scanned Documents. Lecture Notes in Computer Science, 6304, 251–260
  • [9] Liu, C.-B., Ahuja, N. (2004). Vision Based Fire Detection. Proc. of the 17th Int. Conf. on Pattern Recognition, ICPR 2004, Cambridge, UK
  • [10] Oszutowska-Mazurek, D., Mazurek, P., Sycz, K., Waker-Wojciuk, G. (2012). Estimation of Fractal Dimension According to Optical Density of Cell Nuclei in Papanicolaou Smears. Lecture Notes in Computer Science, 7339, 456–463
  • [11] Reverter, F., Rosado, P., Figueras, E., Planas, M.A. (2012). Computer vision methods for image-based artistic ideation. Journal of Theoretical and Applied Computer Science, 6(2), 72–78
  • [12] Rosin, P.L. (1999). Measuring Rectangularity. Machine Vision and Applications, 11, 191–196
  • [13] Rosin, P.L. (2003). Measuring Shape: Ellipticity, Rectangularity and Triangularity. Machine Vision and Applications, 14, 172–184
  • [14] Rosin, P.L. (2005). Computing Global Shape Measures. In: Chen, C.H., Wang, P.S.P. (Eds.) Handbook of Pattern Recognition and Computer Vision, 3rd edn., 177–196
  • [15] Rothe, I., Susse, H., Voss, K. (1996). The Method of Normalization to Determine Invariants. IEEE Trans. On Pattern Analysis and Machine Intelligence, 18, 366–375
  • [16] Sonka, M., Hlavac, V., Boyle, R. (1998). Image Processing, Analysis, and Machine Vision The book (2nd Edition)
  • [17] Wee, C.-Y., Paramesran, R. (2007). On the Computational Aspects of Zernike Moments. Image and Vision Computing, 25 (6), 967–980
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
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Bibliografia
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