Authors:
Rahul Walia
and
Ray Jarvis
Affiliation:
Department of ECSE, Monash University, Australia
Keyword(s):
Scale-Space Theory, Pattern Recognition in Image Understanding, Segmentation and Grouping.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Early Vision and Image Representation
;
Image and Video Analysis
;
Segmentation and Grouping
;
Statistical Approach
Abstract:
A method for gauging the appropriate scale for foreground-background discrimination in Scale-Space theory is presented. Otsu’s Threshold (OT) is a statistical parameter generated from the first two moments of a histogram of a signal / image. In the current work a set of OT is derived from histograms of derivatives of image having Scale-Space representation. This set of OT, when plotted against corresponding scale, generates a Threshold Graph (TG). The TG undergoes an exponential decay, in the absence of foreground and exhibits inflection(s) in the presence of foreground. It is demonstrated, using synthetic and natural images, that the maxima of inflection indicate the scale and threshold (OT) appropriate to interface edges. The edges identified by thresholding at scale and threshold given by inflection of OT correspond to foreground-background interface edges. The histogram inherently imbeds the TG with underlying image signal parameters like background intensity range, pattern fr
equency, foreground-background intensity gradient, foreground size etc, making the method adaptable and deployable for unsupervised machine vision applications. Commutative, separable and symmetric properties of the Scale-Space representation of an image and its derivatives are preserved and computationally efficient implementations are available.
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