Active contours textural and inhomogeneous object extraction

Mahood, Lutful, Ali, Haider, Badshah, Noor, Chen, Ke ORCID: 0000-0002-6093-6623 and Khan, Gulzar Ali
(2016) Active contours textural and inhomogeneous object extraction. PATTERN RECOGNITION, 55. pp. 87-99.

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A new selective segmentation active contour model is proposed in this paper that embeds an enhanced image information. By utilizing the average image of channels (AIC), which handles texture and noise, our model is capable to selectively segment and capture objects with nonuniform features. Moreover, the AIC is fitted with linear functions which are updated regularly to accurately guide the level set function to handle nonconstant intensities. Furthermore, we employ prior information in terms of geometrical constraints which work in alliance with image information to capture objects with intensity inhomogeneity. Experiments show that the proposed method achieves better results than the latest selective segmentation models. In addition, our approach maintains the performance on some hard real and synthetic color images.

Item Type: Article
Uncontrolled Keywords: Image selective segmentation, Level set, Functional minimization, Numerical method
Depositing User: Symplectic Admin
Date Deposited: 06 Oct 2016 15:04
Last Modified: 19 Jan 2023 07:29
DOI: 10.1016/j.patcog.2016.01.021
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