Abstract
In this paper, we present a new segmentation algorithm, based on iterated thresholding and on morphological features. A first thresholding, based on the histogram of the image, is done to partition the image into three sets including respectively pixels belonging to foreground, pixels belonging to background, and unassigned pixels. Thresholding of components of unassigned pixels is then iteratively done, based on the histogram of the components. Components of unassigned pixels, possibly still present at the end of iterated thresholding, are assigned to foreground or background by taking into account area, minimum grey-level and spatial relationship with the adjacent sets.
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Brancati, N., Frucci, M., Sanniti di Baja, G. (2008). Image Segmentation Via Iterative Histogram Thresholding and Morphological Features Analysis. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_13
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DOI: https://doi.org/10.1007/978-3-540-69812-8_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69811-1
Online ISBN: 978-3-540-69812-8
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