Journal
IEEE ACCESS
Volume 7, Issue -, Pages 97492-97504Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2929659
Keywords
Image segmentation; active contour; signed pressure force; intensity inhomogeneity
Categories
Funding
- National Natural Science Foundation of China [61463005, 61866001, 21664002, 61463017]
- China Postdoctoral Science Foundation [2017M612163]
- Natural Science Foundation of Jiangxi Province [20181BAB211017, 20171BAB202028]
- Jiangxi Provincial Key Laboratory of Digital Land [DLLJ201804]
- Science and technology project of Jiangxi Provincial Department of Education [GJJ170450, GJJ160539]
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This study presents a novel active contour model (ACM) driven by weighted global and local region-based signed pressure force (SPF) to segment images in the presence of intensity inhomogeneity and noise. First, an adaptive weighted global region-based SPF (GRSPF) function as the driving centers is designed based on the global image information, which is based on the normalized global intensity to update the weights of the inner and outer regions of the curve during iterations. Second, by introducing the normalized absolute local intensity differences as the weighs of the inner and outer regions, an adaptive weighted local region-based SPF (LRSPF) function is similarly defined. Third, instead of setting a fixed force, a force propagation function is introduced to automatically balance the interior and exterior forces according to the image feature. Meanwhile, by combing the adaptive GWSPF and LWSPF functions, a weighted hybrid region-based SPF function is defined, which can improve the efficiency and accuracy of the proposed model. The experimental results on real images demonstrate that the proposed model is more robust than the popular region-based ACMs for segmenting images with intensity inhomogeneity and noise. The code is available at https://github.com/fangchj2002/WHRSPF.
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