Image Segmentation Via Iterative Histogram Thresholding and Morphological Features Analysis

Authors:
Nadia Brancati;Maria Frucci;Gabriella Sanniti Di Baja
Affiliations:
Institute of Cybernetics "E. Caianiello", CNR, Pozzuoli, Italy;Institute of Cybernetics "E. Caianiello", CNR, Pozzuoli, Italy;Institute of Cybernetics "E. Caianiello", CNR, Pozzuoli, Italy
Venue:
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Year:
2008

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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.