Share Email Print

Optical Engineering

Automatic seeded region growing based on gradient vector flow for color image segmentation
Author(s): Yuan He; Yupin Luo; Dongcheng Hu
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We propose a novel automatic seeded region growing method based on gradient vector flow (GVF) for color image segmentation. YCbCr color space is selected to avoid the high correlation of RGB color space. First, a GVF field is constructed from an edge map of the input image. Then a scaler force field is derived from it by minimizing an energy functional iteratively. From the scalar field, we can select a set of seeds and get an initial segmentation via a straightforward downstream process. Finally, a region adjacency graph–based region merging is applied to merge similar neighboring regions into true results. Experimental results demonstrate that this method is insensitive to noises and efficient to multiple objects segmentation in color images.

Paper Details

Date Published: 1 April 2007
PDF: 7 pages
Opt. Eng. 46(4) 047003 doi: 10.1117/1.2724876
Published in: Optical Engineering Volume 46, Issue 4
Show Author Affiliations
Yuan He, Tsinghua Univ. (China)
Yupin Luo, Tsinghua Univ. (China)
Dongcheng Hu, Tsinghua Univ. (China)

© SPIE. Terms of Use
Back to Top