Journal
SIGNAL IMAGE AND VIDEO PROCESSING
Volume 12, Issue 1, Pages 91-98Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s11760-017-1134-3
Keywords
Fuzzy clustering; Active contour; Local segmentation; Adaptive contrast constraint
Funding
- National Natural Science Foundation of China [81371635, 81671848]
- Key Research and Development Project of Shandong Province [2016GGX101017]
- Research Fund for the Doctoral Program of Higher Education of China [20120131110062]
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Image segmentation is to divide an image into different parts or extract some interested objects. Active contour model and fuzzy clustering are two widely used segmentation methods, which have been integrated into an effective model in recent years. Local segmentation is often needful in medical image processing. In view of local segmentation on inhomogeneous images, a new average fuzzy energy-based active contour model is proposed in this paper, in which the total fuzzy energy integrates the approximate weighted average and arithmetic average variances of the image. And an adaptive contrast constraint condition is introduced to prevent the curve from falling into local minimum, which further improves the robustness of the segmentation model to initial contour. Experimental results on synthetic and medical images demonstrate that the proposed model has considerable improvements in terms of segmentation accuracy and robustness compared to several existing local segmentation models.
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