A new edge-based interactive image segmentation method

Qiang Chen; Quan-sen Sun; De-shen Xia

doi:10.1117/12.866716

19 August 2010 A new edge-based interactive image segmentation method

Qiang Chen, Quan-sen Sun, De-shen Xia

Proceedings Volume 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering; 78201P (2010) https://doi.org/10.1117/12.866716
Event: International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 2010, Xi'an, China

Abstract

This paper presents a new edge-based interactive image segmentation method. First an edge image is generated with an edge detector, and then primary object edges can be selected by separating the object and background edges. Finally we obtain the complete object edge by connecting broken object edges. In order to reduce the influence of the noise, image denoising can be done before the edge detecting. Natural and medical image segmentation demonstrates that our method incorporates the advantages of the automatic and manual image segmentation methods. For most of images, a little of manual object edge connection is needed to obtain object edges. It is an effective and feasible interactive image segmentation method.

Citation Download Citation

Qiang Chen, Quan-sen Sun, and De-shen Xia "A new edge-based interactive image segmentation method", Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78201P (19 August 2010); https://doi.org/10.1117/12.866716

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available