Abstract
Representing images by their interesting points has become recently one of the most effective methods of comparing images. One of the main challenges in image processing is to create a universal descriptor that will be invariant to changes in scale, rotation and illumination. One of the most popular and the most effective algorithm, which generates the key points is currently SURF. The problem discussed in this work concerns the comparison of objects belonging to the same category, but different from each other e.g. two different cars. We propose a new descriptor designed for objects in the image to compare similar objects. It is based on a graph, which was built on the basis of the key points that were generated using SURF algorithm. We present results of experiments which have been conducted for various objects and descriptors generated using the proposed method.
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Nowak, T., Najgebauer, P., Rygał, J., Scherer, R. (2013). A Novel Graph-Based Descriptor for Object Matching. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38658-9_55
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DOI: https://doi.org/10.1007/978-3-642-38658-9_55
Publisher Name: Springer, Berlin, Heidelberg
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