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  1. University of Computer Studies, Yangon
  2. Conferences

Automatic Natural Image Segmentation by Using MarkerControlled Watershed Method and Region Merging Method

http://hdl.handle.net/20.500.12678/0000004411
http://hdl.handle.net/20.500.12678/0000004411
3a1e6d9d-a20f-44a0-973d-7f4933cd99c2
ba3ceab7-bd3b-445d-8f93-ef947de866ac
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Automatic Automatic Natural Image Segmentation by Using MarkerControlled Watershed Method and Region Mergin.pdf (640 Kb)
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Article
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Publication
Title
Title Automatic Natural Image Segmentation by Using MarkerControlled Watershed Method and Region Merging Method
Language en_US
Publication date 2015-02-05
Authors
Mon, Khin Lay
Thaw, Mie Mie
Description
Fully automatic image segmentation is adifficult task for natural images because of manyvariations ascontrast and complex background.Conventional segmentation methods require aconsiderable amount of interactive guidance by theuser to attain satisfactory results. Moreover, the mostsubsequent tasks as object detection and imageanalyzing application highlydepend on the accurateand useful segmented result. Therefore, in this paper,an automatic image segmentation method for naturalimages is proposed. The proposed system includesthree approaches: gradient computation with themodified LoG edge filter, marker-controlled watershedsegmentation(MCWS) with automatically markerselection and region mergingapproach that is based onedge strength and homogeneous intensity. The systemcan not only efficiently reduce the significant oversegmentation problem of watershed algorithm and butalso produce the correct and meaningful segmentedimagesIt purposes better performance of segmentedimages for image annotation, objects detection, imageanalyzing task and computer vision.
Keywords
Region merging, Marker-controlled watershed, Gradient, Mean Intensity
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/2346
Journal articles
Thirteenth International Conference On Computer Applications (ICCA 2015)
Conference papers
Books/reports/chapters
Thesis/dissertations
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