title   
  

Disjunctive normal level set: an efficient parametric implicit method

Mesadi, Fitsum and Çetin, Müjdat and Taşdizen, Tolga (2016) Disjunctive normal level set: an efficient parametric implicit method. In: IEEE International Conference on Image Processing (ICIP 2016), Phoenix, AZ, USA

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Official URL: http://dx.doi.org/10.1109/ICIP.2016.7533171

Abstract

Level set methods are widely used for image segmentation because of their capability to handle topological changes. In this paper, we propose a novel parametric level set method called Disjunctive Normal Level Set (DNLS), and apply it to both two phase (single object) and multiphase (multi-object) image segmentations. The DNLS is formed by union of polytopes which themselves are formed by intersections of half-spaces. The proposed level set framework has the following major advantages compared to other level set methods available in the literature. First, segmentation using DNLS converges much faster. Second, the DNLS level set function remains regular throughout its evolution. Third, the proposed multiphase version of the DNLS is less sensitive to initialization, and its computational cost and memory requirement remains almost constant as the number of objects to be simultaneously segmented grows. The experimental results show the potential of the proposed method.

Item Type:Papers in Conference Proceedings
Uncontrolled Keywords:segmentation, Level set method, parametric level set method, multiphase level set
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
ID Code:30358
Deposited By:Müjdat Çetin
Deposited On:13 Nov 2016 17:56
Last Modified:13 Nov 2016 17:56

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