Abstract

In this paper, we present an automatic seeded region growing (SRG) algorithm for color image segmentation. The method uses regions rather than pixels as the seeds of SRG. The architecture of the algorithm can be described as follows. First, the input RGB color image is transformed into HSI color space. Second, we use watershed segmentation to initialize the image. Third, the initial region seeds are automatically selected according to two rules advanced by us. Fourth, the color image is segmented into regions. Finally, region-merging method is used to merge similar or small regions. Compared with pixel-based SRG algorithm, our method can yield more robust and precise results. Experimental results have also shown that our algorithm can produce excellent results.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.