Multiobject relative fuzzy connectedness and its implications in image segmentation

Jayaram K. Udupa; Punam K. Saha

doi:10.1117/12.431090

3 July 2001 Multiobject relative fuzzy connectedness and its implications in image segmentation

Jayaram K. Udupa, Punam K. Saha

Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431090
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

The notion of fuzzy connectedness captures the idea of hanging-togetherness of image elements in an object by assigning a strength of connectedness to every possible path between every possible pair of image elements. This concept leads to powerful image segmentation algorithms based on dynamic programming whose effectiveness has been demonstrated on 1000s of images in a variety of applications. In a previous framework, we introduced the notion of relative fuzzy connectedness for separating a foreground object from a background object. In this framework, an image element c is considered to belong to that among these two objects with respect to whose reference image element c has the higher strength of connectedness. In fuzzy connectedness, a local fuzzy reflation called affinity is used on the image domain. This relation was required for theoretical reasons to be of fixed form in the previous framework. In the present paper, we generalize relative connectedness to multiple objects, allowing all objects (of importance) to compete among themselves to grab membership of image elements based on their relative strength of connectedness to reference elements. We also allow affinity to be tailored to the individual objects. We present a theoretical and algorithmic framework and demonstrate that the objects defined are independent of the reference elements chosen as long as they are not in the fuzzy boundary between objects. Examples from medical imaging are presented to illustrate visually the effectiveness of multiple object relative fuzzy connectedness. A quantitative evaluation based on 160 mathematical phantom images demonstrates objectively the effectiveness of relative fuzzy connectedness with object- tailored affinity relation.

Citation Download Citation

Jayaram K. Udupa and Punam K. Saha "Multiobject relative fuzzy connectedness and its implications in image segmentation", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431090

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Fuzzy logic

Image segmentation

Binary data

Medical imaging

Zinc

Chemical elements

Bone

Show All Keywords

Keywords/Phrases

Search In:

Publication Years