Using macroscopic information in image segmentation

Khan, Asmar and Xydeas, Costas and Ahmed, Hassan (2013) Using macroscopic information in image segmentation. IET Image Processing, 7 (3). pp. 219-228. ISSN 1751-9667

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Abstract

Post processing “macroscopically” output segmented images obtained from conventional image segmentation (IS) techniques, leads into the concept of Micro-Macro Image Segmentation (MMIS). MMIS pays extra attention to information extracted from relatively large image regions and as a result, overall system segmentation performance improves both subjectively and objectively. The proposed post processing scheme is generic, in the sense that can be used together with any other existing segmentation approach. Thus given an input segmented image, MMIS has the ability to automatically select an appropriate number of regions and classes in a way that helps object oriented visual information to become more apparent in the final segmented output image. Computer simulation results clearly indicate that significant IS performance benefits can be obtained by augmenting conventional IS schemes within an MMIS framework, with or without input images being corrupted by additive Gaussian noise.

Item Type:
Journal Article
Journal or Publication Title:
IET Image Processing
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2208
Subjects:
ID Code:
61371
Deposited By:
Deposited On:
20 Dec 2012 13:51
Refereed?:
Yes
Published?:
Published
Last Modified:
26 Oct 2020 01:16