Abstract
The goal of the shape extraction method presented in this paper was to obtain a concise, robust, and invariant description of planar object shapes for object detection and identification purposes. The solution of this problem was chosen in the form of a piecewise-linear skeleton representation of local shapes in a limited number of salient object locations. A visual attention operator, which can measure the saliency level of image fragments, selects a set of most salient object locations for concise shape description. The proposed operator, called image relevance function, is a multi-scale non-linear matched filter, which takes local maxima at centers of locations of the objects of interest. This attention operator allows a simple extraction of vertices for the skeletal shape description by local maxima analysis.
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Palenichka, R.M., Missaoui, R., Zaremba, M.B. (2004). Extraction of Skeletal Shape Features Using a Visual Attention Operator. In: Fred, A., Caelli, T.M., Duin, R.P.W., Campilho, A.C., de Ridder, D. (eds) Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2004. Lecture Notes in Computer Science, vol 3138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27868-9_11
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DOI: https://doi.org/10.1007/978-3-540-27868-9_11
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