In this paper a novel algorithm for raster to vector conversion is presented. The technique is mainly devoted to vectorize digital picture maintaining an high degree of photorealistic appearance specifically addressed to the human visual system. The algorithm makes use of an advanced segmentation strategy based on statistical region analysis together with a few ad-hoc heuristics devoted to track boundaries of segmented regions. The final output is rendered by Standard Vector Graphics. Experimental results confirm the effectiveness of the proposed approach both in terms of perceived and measured quality. Moreover, the final overall size of the vectorized images outperforms existing methods. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Battiato, S., Farinella, G. M., & Puglisi, G. (2006). Statistical based vectorization for standard vector graphics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3992 LNCS-II, pp. 334–341). Springer Verlag. https://doi.org/10.1007/11758525_44
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