Abstract
We illustrate the problem of comparing images by means of their color segmentations. A group of seven distances are proposed within the frame of the Integrated Region Matching distance and the employ of Multivariate Gaussian Distributions (MGD) for the color description of image regions. The performance of these distances is examined in tasks such as image retrieval and object recognition using the two segmentation algorithms in [1] and [2]. The best overall results are obtained for both tasks using the graph–partition approach along with the Fréchet distance, outperforming other distances in comparing MGDs.
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© 2005 Springer-Verlag Berlin Heidelberg
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Vergés-Llahí, J., Sanfeliu, A. (2005). Evaluation of Distances Between Color Image Segmentations. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_33
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DOI: https://doi.org/10.1007/11492542_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
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