Abstract
A shape decomposition method for non-elongated figures is proposed. The method allows to obtain structural descriptions that are widely invariant with respect to non-significant shape changes occurring in rotated or noisy instances of a same figure. The detection of the significant parts composing a figure is based on a suitable definition of shape primitives and is performed by exploiting the information associated to the skeleton pixels. In this process the regions having higher perceptive relevance are first identified and extracted from the image. Then, starting from this initial decomposition, the remaining parts of the figure are detected together with the structural relations among them. The proposed decomposition scheme is particularly appropriate for building structural descriptions in terms of attributed relational graphs. The experimental results obtained by using a large set of figures confirmed the robustness of the proposed approach and the stability of the achievable decompositions.
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References
H. Blum: Biological shape and visual science (part I), Journal of Theoretical Biology, vol. 38, (1973) 205–287.
M. Brady and H. Asada: Smoothed local symmetries and their implementation, International Journal of Robotic Research, 3, 3, (1984).
D. D. Hoffman and W. A. Richards: Parts of recognition, Cognition, vol. 18, (1985) 65–96.
H. Freeman: Boundary encoding and processing, Picture Processing and Psychopictorics, B. S. Lipkin and A. Rosenfeld eds., Academic Press, (1970) 241–263.
K. Siddiqi, B. Kimia: Toward a Shock Grammar for Recognition, Technical Report LEMS-143, Brown University, (1995).
M. Frucci and A. Marcelli: Efficient skeletonization of binary figures through (d1, d2)-erosion and directional information. In C. Arcelli, L. P. Cordella and G. Sanniti di Baja eds.: Aspects of Visual Form Processing, World Scientific, Singapore, (1994) 221–230.
H. Blum: A transformation for extracting new descriptors of shape. In W. Wathen-Dunn ed.: Models for the Perception of Speech and Visual Form, MIT Press, Cambridge, (1967) 362–380.
M. Frucci and A. Marcelli: Parallel skeletonization by directional information, IEEE Proc. Int. Conf. Image Processing, Austin (USA), (1994) 681–685.
G. Borgerfors: Distance transformations in digital images, CVGIP, vol. 34, (1986) 344–371.
H. Rom and G. Medioni: Hierarchical decomposition and axial shape description, IEEE trans. PAMI, vol.15, no. 10, (1993) 973–981.
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Cordella, L.P., De Stefano, C., Frucci, M. (2000). A Robust Shape Decomposition Method. In: Chhabra, A.K., Dori, D. (eds) Graphics Recognition Recent Advances. GREC 1999. Lecture Notes in Computer Science, vol 1941. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40953-X_18
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DOI: https://doi.org/10.1007/3-540-40953-X_18
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