A similarity-based approach for shape classification using Asian skeletons

Erdem, Aykut
Tarı, Zehra Sibel
Shape skeletons are commonly used in generic shape recognition as they capture part hierarchy, providing a structural representation of shapes. However, their potential for shape classification has not been investigated much. In this study, we present a similarity-based approach for classifying 2D shapes based on their Asian skeletons (Asian and Tan, 2005; Aslan et al., 2008). The coarse structure of this skeleton representation allows us to represent each shape category in the form of a reduced set of prototypical trees, offering an alternative solution to the problem of selecting the best representative examples. The ensemble of these category prototypes is then used to form a similarity-based representation space in which the similarities between a given shape and the prototypes are computed using a tree edit distance algorithm, and support vector machine (SVM) classifiers are used to predict the category membership of the shape based on computed similarities.


Extraction of shape skeletons from grayscale images
Tarı, Zehra Sibel; Pien, H (Elsevier BV, 1997-05-01)
Shape skeletons have been used in computer vision to represent shapes and discover their salient features. Earlier attempts were based on morphological approach in which a shape is eroded successively and uniformly until it is reduced to its skeleton. The main difficulty with this approach is its sensitivity to noise and several approaches have been proposed for dealing with this problem. In this paper, we propose a new method based on diffusion to smooth out the noise and extract shape skeletons in a robus...
A matching algorithm based on linear features
Atalay, Mehmet Volkan (Elsevier BV, 1998-07-01)
A two step feature matching algorithm which is primarily aimed at problems related to the analysis of aerial images of man-made sites is presented. Only linear features and their geometric attributes are used in the algorithm. First, the rotation between the two images is calculated and then matching by relaxation is performed assuming that there is only translation.
A statistical approach to sparse multi-scale phase-based stereo
Ulusoy, İlkay (Elsevier BV, 2007-09-01)
In this study, a multi-scale phase based sparse disparity algorithm and a probabilistic model for matching uncertain phase are proposed. The features used are oriented edges extracted using steerable filters. Feature correspondences are estimated using phase-similarity at multiple scale using a magnitude weighting scheme. In order to achieve sub-pixel accuracy in disparity, we use a fine tuning procedure which employs the phase difference between corresponding feature points. We also derive a probabilistic ...
SASI: a generic texture descriptor for image retrieval
Carkacioglu, A; Yarman-Vural, F (Elsevier BV, 2003-11-01)
In this paper, a generic texture descriptor, namely, Statistical Analysis of Structural Information (SASI) is introduced as a representation of texture. SASI is based on statistics of clique autocorrelation coefficients, calculated over structuring windows. SASI defines a set of clique windows to extract and measure various structural properties of texture by using a spatial multi-resolution method. Experimental results, performed on various image databases, indicate that SASI is more successful then the Ga...
Automatic segmentation of VHR images using type information of local structures acquired by mathematical morphology
AYTEKİN, orsan; Ulusoy, İlkay (Elsevier BV, 2011-10-01)
The morphological profile (MP) and differential morphological profile (DMP) have been used extensively to acquire spatial information to be used in the segmentation of very high resolution (VHR) remotely sensed images. In most of the previous approaches, the maxima of the MP and DMP were investigated to estimate the best representative scale in the spatial domain for the pixel under consideration. Then, the object type (i.e. dark, bright or flat) was estimated based on the location of the maximum. Finally, ...
Citation Formats
A. Erdem and Z. S. Tarı, “A similarity-based approach for shape classification using Asian skeletons,” PATTERN RECOGNITION LETTERS, pp. 2024–2032, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57970.