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Summary: Color Image Segmentation Based on
Adaptive Local Thresholds
ETY NAVON, OFER MILLER*
, AMIR AVERBUCH
School of Computer Science
Tel-Aviv University, Tel-Aviv, 69978, Israel
E-Mail*
: millero@post.tau.ac.il Fax number: 972-3-9160284
Abstract
The goal of still color image segmentation is to divide the image into homogeneous regions.
Object extraction, object recognition and object-based compression are typical applications
that use still segmentation as a low-level image processing. In this paper we present a new
method for color image segmentation. The proposed algorithm divides the image into
homogeneous regions by local thresholds. The number of thresholds and their values are
adaptively derived by an automatic process, where local information is taken into
consideration. First, the watershed algorithm is applied. Its results are used as an
initialization for the next step, which is iterative merging process. During the iterative
process regions are merged and local thresholds are derived. The thresholds are determined
one-by-one at different times during the merging process. Every threshold is calculated by
local information on any region and its surroundings. Any statistical information on the
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