Fuzzy Bit-Plane-Dependence Region Competition

Siukai Choy, Tszching Ng, Carisa Yu and Benson Lam
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Siukai Choy: Department of Mathematics, Statistics and Insurance, The Hang Seng University of Hong Kong, Hong Kong 999077, China
Tszching Ng: Department of Mathematics, Statistics and Insurance, The Hang Seng University of Hong Kong, Hong Kong 999077, China
Carisa Yu: Department of Mathematics, Statistics and Insurance, The Hang Seng University of Hong Kong, Hong Kong 999077, China
Benson Lam: Department of Mathematics, Statistics and Insurance, The Hang Seng University of Hong Kong, Hong Kong 999077, China

Mathematics, 2021, vol. 9, issue 19, 1-19

Abstract: This paper presents a novel variational model based on fuzzy region competition and statistical image variation modeling for image segmentation. In the energy functional of the proposed model, each region is characterized by the pixel-level color feature and region-level spatial/frequency information extracted from various image domains, which are modeled by the windowed bit-plane-dependence probability models. To efficiently minimize the energy functional, we apply an alternating minimization procedure with the use of Chambolle’s fast duality projection algorithm, where the closed-form solutions of the energy functional are obtained. Our method gives soft segmentation result via the fuzzy membership function, and moreover, the use of multi-domain statistical region characterization provides additional information that can enhance the segmentation accuracy. Experimental results indicate that the proposed method has a superior performance and outperforms the current state-of-the-art superpixel-based and deep-learning-based approaches.

Keywords: bit-plane; fuzzy region competition; image segmentation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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