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Titlebook: Combinatorial Image Analysis; 16th International W Reneta P. Barneva,Valentin E. Brimkov,Josef Šlapal Conference proceedings 2014 Springer

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Kind en adolescent praktijkreekse segmentation, this bunch of elementary objects is identified as one object, which has completely different geometrical properties from the elementary objects. The information about the number of objects, their size and shape is degraded. The paper considers a step towards solving this problem. It
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https://doi.org/10.1007/978-981-19-3463-6 opportunities for exploiting novel features..Using the information gained from a conventional camera we have data about the colours, the shape of objects and the micro-structures; and we have additional information while using thermal camera in the darkness. A camera with depth sensor can find the
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https://doi.org/10.1007/978-3-658-19587-8n enables to capture the entire object. On the other hand, handling 3D images also requires new algorithms, since not all of them can be modified for higher dimensions intuitively. In this article, we introduce a comparison of various implementations of 3D texture descriptors presented in the litera
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Superiorization for Image Analysisproduce a solution that is constraints-compatible. It is typically the case that a large number of solutions would be considered good enough from the point of view of being constraints-compatible. In such a case, an optimization criterion is introduced that helps us to distinguish the “better” const
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Parallel Algorithms for Combinatorial Pattern Matchingin pattern recognition, low level image processing, computer vision and, more recently, multimedia. After introducing some basic notions and concepts and recalling related key facts, we briefly discuss the basic steps of a parallel algorithm design, illustrating them by author’s results on the probl
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