Fast Mumford-Shah two-phase image segmentation using proximal splitting scheme
type: Item
instance of: scholarly article
title: Fast Mumford-Shah two-phase image segmentation using proximal splitting scheme
zbMATH Open document ID: 1499.94013
DOI: 10.1155/2021/6618505
author: Nilima Shah
author: Dhanesh Patel
author: Pasi Fränti
published in: Journal of Applied Mathematics
publication date: 2021-07-05T00:00:00Z
review text: Summary: The Mumford-Shah model is extensively used in image segmentation. Its energy functional causes the content of the segments to remain homogeneous and the segment boundaries to become short. However, the problem is that optimization of the functional can be very slow. To attack this problem, we propose a reduced two-phase Mumford-Shah model to segment images having one prominent object. First, initial segmentation is obtained by the k-means clustering technique, further minimizing the Mumford-Shah functional by the Douglas-Rachford algorithm. Evaluation of segmentations with various error metrics shows that 70 percent of the segmentations keep the error values below 50\%. Compared to the level set method to solve the Chan-Vese model, our algorithm is significantly faster. At the same time, it gives almost the same or better segmentation results. When compared to the recent k-means variant, it also gives much better segmentation with convex boundaries. The proposed algorithm balances well between time and quality of the segmentation. A crucial step in the design of machine vision systems is the extraction of discriminant features from the images, which is based on low-level segmentation which can be obtained by our approach.
Mathematics Subject Classification ID: 94A08
Mathematics Subject Classification ID: 68U10
zbMATH DE Number: 7368039
describes a project that uses: BSDS
describes a project that uses: UNLocBoX
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2021/6618505
OpenAlex ID: W3153975561
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description: scientific article; zbMATH DE number 7368039