Hierarchical Segmentation of Falsely Touching Characters from Camera Captured Degraded Document Images
An innovative hierarchical image segmentation scheme is
reported in this research communication. Unlike static/ spatially
divided sub-images, the current innovation concentrates on
object level hierarchy for segmentation of gray scale or color
images into constituent component/ sub-parts. As for example, a
gray scale document image may be segmented (binarized in case
of two-level segmentation) into connected foreground
components (text/ graphics) and background component by
hierarchically applying a gray level threshold selection algorithm
in the object-space. In any hierarchy, constituent objects are
identified as connected foreground pixels, as classified by the
gray scale threshold selection algorithm. To preserve the global
information, thresholds for each object in any hierarchy are
estimated as a weighted aggregate of the current and previous
thresholds relevant to the object. The developed technique may
be customized as a general purpose hierarchical information
clustering algorithm in the domain of pattern analysis, data
mining, bioinformatics etc.
Keywords: Binarization, Connected component labeling, Hierarchical object, Weighted average threshold
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