NDLI: Active contours driven by harmonic mean based KL divergence fitting energies for image segmentation

Content Provider	IET Digital Library
Author	Han, Bin Wu, Yiquan
Abstract	A new active contour model driven by harmonic mean based Kullback–Leibler (KL) fitting energies is presented to achieve accurate segmentation of various kinds of images. Firstly, the global fitted image is defined by global harmonic mean region fitting centres and the piece-wise smooth function and then the global fitting term can be constructed based on KL divergence. Secondly, the local fitted image is defined by local harmonic mean region fitting centres and the piece-wise smooth function and then the local fitting term is also constructed based on KL divergence. Moreover, the regularising term is incorporated into the energy functional. Experimental results of real-world images verify the effectiveness and superiority of the presented model.
Starting Page	817
Ending Page	819
Page Count	3
ISSN	00135194
Volume Number	54
e-ISSN	1350911X
Issue Number	Issue 13, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/54/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2018.1108
Journal	Electronics Letters
Publisher Date	2018-05-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Active Contour Model Active Contours Computer Vision And Image Processing Technique Edge Detection Energy Functional Global Fitted Image Global Fitting Term Global Harmonic Mean Region Fitting Centres Harmonic Mean Based KL Divergence Fitting Energy Image Recognition Image Segmentation KL Divergence Kullback–Leibler Fitting Energies Local Fitted Image Local Fitting Term Local Harmonic Mean Region Fitting Centres Piece-wise Smooth Function Real-world Image
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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