Abstract
In this paper, a new method for the segmentation of color images is presented. This method searches for an acceptable segmentation of 1D-histograms, according to a “monotone” hypothesis. The algorithm uses recurrence to localize all the modes in the histogram. The algorithm is applied on the hue, saturation and intensity histograms of the image. As a result, an optimal and accurately segmented image is obtained. In contrast to previous state of the art methods uses exclusively the image color histogram to perform segmentation and no spatial information at all.
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Delon, J., Desolneux, A., Lisani, J.L., Petro, A.B. (2005). Color Image Segmentation Using Acceptable Histogram Segmentation. 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_30
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DOI: https://doi.org/10.1007/11492542_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
Online ISBN: 978-3-540-32238-2
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