Author
J Fan, DKY Yau, AK Elmagarmid, WG Aref
Abstract
We propose a new automatic image segmentation
method. Color edges in an image are first obtained automatically
by combining an improved isotropic edge detector and a fast
entropic thresholding technique. After the obtained color edges
have provided the major geometric structures in an image, the
centroids between these adjacent edge regions are taken as the
initial seeds for seeded region growing (SRG). These seeds are
then replaced by the centroids of the generated homogeneous
image regions by incorporating the required additional pixels
step by step. Moreover, the results of color-edge extraction and
SRG are integrated to provide homogeneous image regions with
accurate and closed boundaries. We also discuss the application
of our image segmentation method to automatic face detection.
Furthermore, semantic human objects are generated by a seeded
region aggregation procedure which takes the detected faces as
object seeds.