Close Search Advanced
Journals
Resources
About Us
Open Access

Image Selective Segmentation Under Geometrical Constraints Using an Active Contour Approach

Image Selective Segmentation Under Geometrical Constraints Using an Active Contour Approach
Preview
Add to basket

Year:    2010

Communications in Computational Physics, Vol. 7 (2010), Iss. 4 : pp. 759–778

Abstract

In this paper we propose a new model for segmentation of an image under some geometrical constraints in order to detect special regions of interest. Our work is based on the recent work by Gout et al. [Numer. Algorithms, 39 (2005), pp. 155-173 and 48 (2008), pp. 105-133] using geodesic active contours models, by combining it with the idea of a piecewise constant Mumford-Shah model as with the non-selective Chan-Vese segmentation. Numerical tests show that our method is more robust than the previous works.

Submit Article

You do not have full access to this article.

Already a Subscriber? Sign in as an individual or via your institution

Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.2009.09.026

Communications in Computational Physics, Vol. 7 (2010), Iss. 4 : pp. 759–778

Published online:    2010-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    20

Keywords:   

  1. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

    Fast Numerical Methods for Image Segmentation Models

    Badshah, Noor

    2022

    https://doi.org/10.1007/978-3-030-03009-4_121-1 [Citations: 0]

  2. A Level Set Approach for Segmentation of Intensity Inhomogeneous Image Based on Region Decomposition

    Chakravarty, Deepa | Pradhan, Debasish

    SN Computer Science, Vol. 1 (2020), Iss. 5

    https://doi.org/10.1007/s42979-020-00278-w [Citations: 2]

  3. A modified multi-grid algorithm for a novel variational model to remove multiplicative noise

    Ullah, Asmat | Chen, Wen | Sun, HongGuang | Khan, Mushtaq Ahmad

    Journal of Visual Communication and Image Representation, Vol. 40 (2016), Iss. P.485

    https://doi.org/10.1016/j.jvcir.2016.07.016 [Citations: 8]

  4. Selective Image Segmentation Models Using Three Distance Functions

    Abdullah, Siti Aminah | Jumaat, Abdul Kadir

    Journal of Information and Communication Technology, Vol. 21 (2021), Iss.

    https://doi.org/10.32890/jict2022.21.1.5 [Citations: 1]

  5. Robust region-based active contour models via local statistical similarity and local similarity factor for intensity inhomogeneity and high noise image segmentation

    Hussain, Ibrar | Ali, Haider | Khan, Muhammad Shahkar | Niu, Sijie | Rada, Lavdie

    Inverse Problems and Imaging, Vol. 16 (2022), Iss. 5 P.1113

    https://doi.org/10.3934/ipi.2022014 [Citations: 2]

  6. A survey of recent interactive image segmentation methods

    Ramadan, Hiba | Lachqar, Chaymae | Tairi, Hamid

    Computational Visual Media, Vol. 6 (2020), Iss. 4 P.355

    https://doi.org/10.1007/s41095-020-0177-5 [Citations: 43]

  7. A local information based variational model for selective image segmentation

    Gould, Derek A. | Yu, Bo | Chen, Ke | Zhang, Jianping

    Inverse Problems and Imaging, Vol. 8 (2014), Iss. 1 P.293

    https://doi.org/10.3934/ipi.2014.8.293 [Citations: 11]

  8. Efficiently Guided Active Contours for Image Segmentation

    Mabood, Lutful | Ullah, Tahir | Ali, Haider | Badshah, Noor

    Punjab University Journal of Mathematics, Vol. (2022), Iss. P.477

    https://doi.org/10.52280/pujm.2021.540704 [Citations: 0]

  9. Efficient Dual Algorithms for Image Segmentation Using TV-Allen-Cahn Type Models

    Wang, Li-Lian | Gu, Ying

    Communications in Computational Physics, Vol. 9 (2011), Iss. 4 P.859

    https://doi.org/10.4208/cicp.221109.290710a [Citations: 10]

  10. An adaptive-scale active contour model for inhomogeneous image segmentation and bias field estimation

    Cai, Qing | Liu, Huiying | Zhou, Sanping | Sun, Jingfeng | Li, Jing

    Pattern Recognition, Vol. 82 (2018), Iss. P.79

    https://doi.org/10.1016/j.patcog.2018.05.008 [Citations: 68]

  11. Topology- and convexity-preserving image segmentation based on image registration

    Zhang, Daoping | Tai, Xue-cheng | Lui, Lok Ming

    Applied Mathematical Modelling, Vol. 100 (2021), Iss. P.218

    https://doi.org/10.1016/j.apm.2021.08.017 [Citations: 11]

  12. A new variational method for selective segmentation of medical images

    Zhao, Wenxiu | Wang, Weiwei | Feng, Xiangchu | Han, Yu

    Signal Processing, Vol. 190 (2022), Iss. P.108292

    https://doi.org/10.1016/j.sigpro.2021.108292 [Citations: 8]
  13. Scale Space and Variational Methods in Computer Vision

    Robust Edge Detection Using Mumford-Shah Model and Binary Level Set Method

    Wang, Li-Lian | Shi, Yuying | Tai, Xue-Cheng

    2012

    https://doi.org/10.1007/978-3-642-24785-9_25 [Citations: 8]

  14. Selective variational image segmentation combined with registration: Models and algorithms

    Chen, Ke

    2012 3rd International Conference on Image Processing Theory, Tools and Applications (IPTA), (2012), P.5

    https://doi.org/10.1109/IPTA.2012.6469481 [Citations: 1]

  15. Two-Phase Image Inpainting: Combine Edge-Fitting with PDE Inpainting

    Wang, Meiqing | Huang, Chensi | Zeng, Chao | Lai, Choi-Hong

    Advances in Applied Mathematics and Mechanics, Vol. 4 (2012), Iss. 06 P.769

    https://doi.org/10.4208/aamm.12-12S08 [Citations: 1]
  16. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

    A Survey of Topology and Geometry-Constrained Segmentation Methods in Weakly Supervised Settings

    Chen, Ke | Debroux, Noémie | Le Guyader, Carole

    2021

    https://doi.org/10.1007/978-3-030-03009-4_85-1 [Citations: 1]

  17. Selective Segmentation Model for Vector-Valued Images

    Mohd Ghani , Noor Ain Syazwani | Jumaat, Abdul Kadir

    Journal of Information and Communication Technology, Vol. 21 (2022), Iss.

    https://doi.org/10.32890/jict2022.21.2.1 [Citations: 1]

  18. A 3D multi-grid algorithm for the Chan–Vese model of variational image segmentation

    Zhang, Jianping | Chen, Ke | Yu, Bo

    International Journal of Computer Mathematics, Vol. 89 (2012), Iss. 2 P.160

    https://doi.org/10.1080/00207160.2011.632410 [Citations: 10]

  19. A Convex Geodesic Selective Model for Image Segmentation

    Roberts, Michael | Chen, Ke | Irion, Klaus L.

    Journal of Mathematical Imaging and Vision, Vol. 61 (2019), Iss. 4 P.482

    https://doi.org/10.1007/s10851-018-0857-2 [Citations: 23]

  20. Mathematical Model for Single and Multiple Object Extraction

    Shujahuddin, Amna | Khan, Muhammad Salim | Ali, Haider

    Punjab University Journal of Mathematics, Vol. (2021), Iss. P.387

    https://doi.org/10.52280/pujm.2021.530603 [Citations: 0]
  21. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

    A Survey of Topology and Geometry-Constrained Segmentation Methods in Weakly Supervised Settings

    Chen, Ke | Debroux, Noémie | Le Guyader, Carole

    2023

    https://doi.org/10.1007/978-3-030-98661-2_85 [Citations: 1]
  22. Scale Space and Variational Methods in Computer Vision

    A Deep Image Prior Learning Algorithm for Joint Selective Segmentation and Registration

    Burrows, Liam | Chen, Ke | Torella, Francesco

    2021

    https://doi.org/10.1007/978-3-030-75549-2_33 [Citations: 0]
  23. Medical Image Understanding and Analysis

    Edge Enhancement for Image Segmentation Using a RKHS Method

    Burrows, Liam | Guo, Weihong | Chen, Ke | Torella, Francesco

    2020

    https://doi.org/10.1007/978-3-030-39343-4_17 [Citations: 1]
  24. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging

    Fast Numerical Methods for Image Segmentation Models

    Badshah, Noor

    2023

    https://doi.org/10.1007/978-3-030-98661-2_121 [Citations: 0]

  25. A Retinex-Based Selective Segmentation Model for Inhomogeneous Images

    Min, Lihua | Lian, Xiaoyu | Jin, Zhengmeng | Zheng, Minling

    Journal of Mathematical Imaging and Vision, Vol. 65 (2023), Iss. 3 P.437

    https://doi.org/10.1007/s10851-022-01127-6 [Citations: 1]
  26. Medical Image Understanding and Analysis

    On New Convolutional Neural Network Based Algorithms for Selective Segmentation of Images

    Burrows, Liam | Chen, Ke | Torella, Francesco

    2020

    https://doi.org/10.1007/978-3-030-52791-4_8 [Citations: 3]

  27. Selective Image Segmentation Models Using Three Distance Functions

    Abdullah, Siti Aminah | Jumaat, Abdul Kadir

    Journal of Information and Communication Technology, Vol. 21 (2021), Iss.

    https://doi.org/10.32890/jict2022.21.1.5 [Citations: 1]

  28. A fast edge detection algorithm using binary labels

    Shi, Yuying | Gu, Ying | Wang, Li-Lian | Tai, Xue-Cheng

    Inverse Problems & Imaging, Vol. 9 (2015), Iss. 2 P.551

    https://doi.org/10.3934/ipi.2015.9.551 [Citations: 10]

  29. A convex selective segmentation model based on a piece-wise constant metric-guided edge detector function

    Khan, Muhammad Shahkar | Ali, Haider | Zakarya, Muhammad | Tirunagari, Santosh | Khan, Ayaz Ali | Khan, Rahim | Ahmed, Aftab | Rada, Lavdie

    Soft Computing, Vol. (2023), Iss.

    https://doi.org/10.1007/s00500-023-08173-1 [Citations: 0]

  30. Edge detection with mixed noise based on maximum a posteriori approach

    Shi, Yuying | Liu, Zijin | Wang, Xiaoying | Zhang, Jinping

    Inverse Problems & Imaging, Vol. 15 (2021), Iss. 5 P.1223

    https://doi.org/10.3934/ipi.2021035 [Citations: 0]

  31. A Selective Segmentation Model Using Dual-Level Set Functions and Local Spatial Distance

    Rahman, Afzal | Ali, Haider | Badshah, Noor | Rada, Lavdie | Khan, Ayaz Ali | Hussain, Hameed | Zakarya, Muhammad | Ahmed, Aftab | Rahman, Izaz Ur | Raza, Mushtaq | Haleem, Muhammad

    IEEE Access, Vol. 10 (2022), Iss. P.22344

    https://doi.org/10.1109/ACCESS.2022.3152785 [Citations: 8]

  32. Feature extraction from MR images for detection of brain and breast tumors through mathematical modeling

    Badshah, Noor | Rabbani, Hena | Atta, Hadia | Irfan, Muhammad Abeer | Ahmad, Ali

    Biomedical Signal Processing and Control, Vol. 86 (2023), Iss. P.105344

    https://doi.org/10.1016/j.bspc.2023.105344 [Citations: 0]

  33. Topology-Preserving 3D Image Segmentation Based on Hyperelastic Regularization

    Zhang, Daoping | Lui, Lok Ming

    Journal of Scientific Computing, Vol. 87 (2021), Iss. 3

    https://doi.org/10.1007/s10915-021-01433-y [Citations: 7]

  34. Selective segmentation of a feature that has two distinct intensities

    Burrows, Liam | Chen, Ke | Torella, Francesco

    Journal of Algorithms & Computational Technology, Vol. 15 (2021), Iss.

    https://doi.org/10.1177/17483026211007776 [Citations: 0]

  35. On local active contour model for automatic detection of tumor in MRI and mammogram images

    Badshah, Noor | Rabbani, Hena | Atta, Hadia

    Biomedical Signal Processing and Control, Vol. 60 (2020), Iss. P.101993

    https://doi.org/10.1016/j.bspc.2020.101993 [Citations: 7]

  36. On an effective multigrid solver for solving a class of variational problems with application to image segmentation

    Roberts, Michael | Chen, Ke | Li, Jingzhi | Irion, Klaus L.

    International Journal of Computer Mathematics, Vol. 97 (2020), Iss. 10 P.2015

    https://doi.org/10.1080/00207160.2019.1674290 [Citations: 1]

  37. Image Segmentation for Intensity Inhomogeneity in Presence of High Noise

    Ali, Haider | Rada, Lavdie | Badshah, Noor

    IEEE Transactions on Image Processing, Vol. 27 (2018), Iss. 8 P.3729

    https://doi.org/10.1109/TIP.2018.2825101 [Citations: 63]

  38. A fast algorithm for automatic segmentation and extraction of a single object by active surfaces

    Zhang, Jianping | Chen, Ke | Gould, Derek A.

    International Journal of Computer Mathematics, Vol. 92 (2015), Iss. 6 P.1251

    https://doi.org/10.1080/00207160.2014.931943 [Citations: 8]

  39. Infinite perimeter selective segmentation model

    RADA, Lavdie

    Natural and Applied Sciences Journal, Vol. 4 (2021), Iss. 2 P.32

    https://doi.org/10.38061/idunas.932338 [Citations: 0]

  40. Self-adaptive weighted level set evolution based on local intensity difference for parotid ducts segmentation

    Deng, Xuan | Lan, Tianjun | Chen, Zhifeng | Zhang, Minghui | Tao, Qian | Lu, Zhentai

    Computers in Biology and Medicine, Vol. 114 (2019), Iss. P.103432

    https://doi.org/10.1016/j.compbiomed.2019.103432 [Citations: 3]

  41. A general framework of piecewise-polynomial Mumford–Shah model for image segmentation

    Chen, Chong | Leng, Juelin | Xu, Guoliang

    International Journal of Computer Mathematics, Vol. 94 (2017), Iss. 10 P.1981

    https://doi.org/10.1080/00207160.2016.1274741 [Citations: 7]

  42. Grouping Boundary Proposals for Fast Interactive Image Segmentation

    Liu, Li | Chen, Da | Shu, Minglei | Cohen, Laurent D.

    IEEE Transactions on Image Processing, Vol. 33 (2024), Iss. P.793

    https://doi.org/10.1109/TIP.2024.3349867 [Citations: 0]

  43. Multigrid algorithm based on hybrid smoothers for variational and selective segmentation models

    Roberts, Michael | Chen, Ke | Irion, Klaus L.

    International Journal of Computer Mathematics, Vol. 96 (2019), Iss. 8 P.1623

    https://doi.org/10.1080/00207160.2018.1494827 [Citations: 3]

  44. An Improved Model for Image Selective Segmentation Based on Local and Global Statistics

    Li, Shurong | Meng, Yu | Zhang, Minyi

    2019 Chinese Control And Decision Conference (CCDC), (2019), P.2701

    https://doi.org/10.1109/CCDC.2019.8833009 [Citations: 0]

  45. An active contour model and its algorithms with local and global Gaussian distribution fitting energies

    Wang, Hui | Huang, Ting-Zhu | Xu, Zongben | Wang, Yilun

    Information Sciences, Vol. 263 (2014), Iss. P.43

    https://doi.org/10.1016/j.ins.2013.10.033 [Citations: 78]