By Topic

Multiscale image segmentation by integrated edge and region detection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Tabb, M. ; Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA ; Ahuja, N.

This paper is concerned with the detection of low-level structure in images. It describes an algorithm for image segmentation at multiple scales. The detected regions are homogeneous and surrounded by closed edge contours. Previous approaches to multiscale segmentation represent an image at different scales using a scale-space. However, structure is only represented implicitly in this representation, structures at coarser scales are inherently smoothed, and the problem of structure extraction is unaddressed. This paper argues that the issues of scale selection and structure detection cannot be treated separately. A new concept of scale is presented that represents image structures at different scales, and not the image itself. This scale is integrated into a nonlinear transform which makes structure explicit in the transformed domain. Structures that are stable (locally invariant) to changes in scale are identified as being perceptually relevant. The transform can be viewed as collecting spatially distributed evidence for edges and regions, and making it available at contour locations, thereby facilitating integrated detection of edges and regions without restrictive models of geometry or homogeneity. In this sense, it performs Gestalt analysis. All scale parameters of the transform are automatically determined, and the structure of any arbitrary geometry can be identified without any smoothing, even at coarse scales

Published in:

Image Processing, IEEE Transactions on  (Volume:6 ,  Issue: 5 )