Abstract
In this article we present the results of an unsupervised segmentation algorithm based on a multiresolution method. The algorithm uses color and edge information in an iterative minimization process of an energy function. The process has been applied to fruit images to distinguish the different areas of the fruit surface in fruit quality assessment applications. Due to the unsupervised nature of the procedure, it can adapt itself to the huge variability of colors and shapes of the regions in fruit inspection applications.
This work has been partly supported by grants DPI2001-2956-C02-02 from Spanish CICYT and IST-2001-37306 from the European Union
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Martínez-Usó, A., Pla, F., García-Sevilla, P. (2004). Color Image Segmentation Using Energy Minimization on a Quadtree Representation. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2004. Lecture Notes in Computer Science, vol 3211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30125-7_4
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DOI: https://doi.org/10.1007/978-3-540-30125-7_4
Publisher Name: Springer, Berlin, Heidelberg
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