Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Using macroscopic information in image segmentation
AU - Khan, Asmar
AU - Xydeas, Costas
AU - Ahmed, Hassan
PY - 2013/4
Y1 - 2013/4
N2 - 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.
AB - 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.
U2 - 10.1049/iet-ipr.2012.0243
DO - 10.1049/iet-ipr.2012.0243
M3 - Journal article
VL - 7
SP - 219
EP - 228
JO - IET Image Processing
JF - IET Image Processing
SN - 1751-9667
IS - 3
ER -