![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextgreen.png)
![Open Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_open_medium.gif)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltextred.png)
![Restricted Access](https://i-scholar.in/lib/pkp/templates/images/icons/fulltext_restricted_medium.gif)
Fractional Differentiation-Based Edge Energy Driven Active Contours for Robust Image Segmentation
Subscribe/Renew Journal
In this paper, a new fractional differentiation-based active contour model for robust image segmentation is presented. A new edge energy is introduced, in which the contour evolution is driven by the difference between the fractional derivatives directed along the inward and outward normal directions of the evolving contour. We provide the level set formulation of this novel energy and show that this energy is minimized when there is an accurate alignment of the zeroth level set of the evolving contour with the actual object boundary. The proposed model outperforms other state-of-the-art active contour methods in eliciting weak/fuzzy boundaries in real world images and provides robust segmentation even under influence of various types of noise as quantified by segmentation metrics.
Keywords
Fractional Derivative, Image Segmentation, Active Contour, Edge Energy.
Subscription
Login to verify subscription
User
Font Size
Information
- M. Kass, A. Witkin and D. Terzopoulos, “Snakes: Active Contour Models”, International Journal of Computer Vision, Vol. 1, No. 4, pp. 321-331, 1988.
- S. Osher and J.A. Sethian, “Fronts Propagating with Curvature-Dependent Speed: Algorithms based on Hamilton-Jacobi Formulations”, Journal of Computational Physics, Vol. 79, No. 1, pp. 12-49, 1988.
- V. Caselles, R. Kimmel and G. Sapiro, “Geodesic Active Contours”, International Journal of Computer Vision, Vol. 22, No. 1, pp. 61-79, 1997.
- S. Kichenassamy, A. Kumar, P. Oliver, A. Tannenbaum and A. Yezzi, “Gradient Flows and Geometric Active Contour Models”, Proceedings of 5th International Conference on Computer Vision, pp. 810-815, 1995.
- C. Li, C. Xu, C. Gui and M.D. Fox, “Level Set Evolution without Re-Initialization: A New Variational Formulation”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Vol. 1, pp. 430-436, 2005.
- C. Li, C. Xu, C. Gui and M.D. Fox, “Distance Regularized Level Set Evolution and Its Application to Image Segmentation”, IEEE Transactions on Image Processing, Vol. 19, No. 12, pp. 3243-3254, 2010.
- R. Ronfard, “Region-Based Strategies for Active Contour Models”, International Journal of Computer Vision, Vol. 13, pp. 229-251, 1994.
- T.F. Chan and L.A. Vese, “Active Contours without Edges”, IEEE Transactions on Image Processing, Vol. 10, No. 2, pp. 266-277, 2001.
- A. Yezzi, A. Tsai and A. Willsky, “A Statistical Approach to Snakes for Bimodal and Trimodal Imagery”, Proceedings of International Conference on Computer Vision, Vol. 2, pp. 898-903, 1999.
- D. Cremers, M. Rousson and R. Deriche, “A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion, and Shape”, International Journal of Computer Vision, Vol. 72, No. 2, pp. 195-215, 2007.
- S. Lankton and A. Tannenbaum, “Localizing Region-based Active Contours”, IEEE Transactions Image Processing, Vol. 17, No. 11, pp. 2029-2039, 2008.
- S. Lankton, D. Nain, A. Yezzi and A. Tannenbaum, “Hybrid Geodesic Region-based Curve Evolutions for Image Segmentation”, Proceedings of SPIE, Vol. 6510, pp. 1-8, 2007.
- W. Kim and C. Kim, “Active Contours Driven by the Salient Edge Energy Model”, IEEE Transactions on Image Processing, Vol. 22, No. 4, pp. 1667-1673, 2013.
- Zemin Ren, “Adaptive Active Contour Model Driven by Fractional Order Fitting Energy”, Signal Processing, Vol. 117, pp. 138-150, 2015.
- Bo Chen, Shan Huang, Zhengrong Liang, Wensheng Chen, Hanling Lin, Binbin Pan and Marc Pomeroy, “A Fractional Active Contour Model for Medical Image Segmentation”, Proceedings of IEEE Conference on Nuclear Science Symposium and Medical Imaging, pp. 1-6, 2017.
- Ming Gu and Renfang Wang, “Fractional Differentiation-Based Active Contour Model Driven by Local Intensity Fitting Energy”, Mathematical Problems in Engineering, Vol. 2016, pp. 1-16, 2016.
- Bo Chen, Lihong C. Li, Huafeng Wang, Xinzhou Wei, Shan Huang, Wensheng Chen and Zhengrong Liang, “A New Fractional-Order Derivative-based Active Contour Model for Colon Wall Segmentation”, Proceedings of IEEE Conference on Medical Imaging, pp. 1-7, 2018.
- A. Khadidos, V. Sanchez and C. Li, “Weighted Level Set Evolution Based on Local Edge Features for Medical Image Segmentation”, IEEE Transactions on Image Processing, Vol. 26, No. 4, pp. 1979-1991, 2017.
- M.D. Ortigueira and J.A.T. Machado, “What is a Fractional Derivative?”, Journal of Computational Physics, Vol. 321, pp. 1255-1257, 2016.
- R. Hilfer and Y. Luchko, “Desiderata for Fractional Derivatives and Integrals”, Mathematics, Vol. 7, No. 2, pp. 1-14, 2019.
- B. Mathieu, P. Melchior, A. Oustaloup and C.H. Ceyral, “Fractional Differentiation for Edge Detection”, Signal Processing, Vol. 83, No. 11, pp. 2421-2432, 2003.
- Y. Pu and J. Zhou and X. Yuan, “Fractional Differential Mask: A Fractional Differential-Based Approach for Multiscale Texture Enhancement”, IEEE Transactions on Image Processing, Vol. 19, No. 2, pp. 491-511, 2010.
- S. Khanna and V. Chandrasekaran, “Fractional Derivative Filter for Image Contrast Enhancement with Order Prediction”, Proceedings of IET Conference on Image Processing, pp. 1-6, 2012.
- J. Wang, Y. Ye and X. Gao, “Fractional 90 Phase-Shift Filtering based on the Double-Sided Grunwald-Letnikov Differintegrator”, IET Signal Processing, Vol. 9, No. 4, pp. 328-334, 2015.
- J. Li, N. Sang and C. Gao, “Local Fractional Order Derivative Vector Quantization Pattern for Face Recognition”, Proceedings of IEEE Conference on Computer Vision, pp. 1-13, 2017.
- C. Li, C. Kao, J. C. Gore and Z. Ding, “Minimization of Region-Scalable Fitting Energy for Image Segmentation”, IEEE Transactions on Image Processing, Vol. 17, No. 10, pp. 1940-1949, 2008.
- H. Park, T. Schoepflin and Y. Kim, “Active Contour Model with Gradient Directional Information: Directional Snake”, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 11, No. 2, pp. 252-256, 2001.
- R. Kimmel, “Fast Edge Integration”, Proceedings of IEEE Conference on Geometric Level Set Methods in Imaging, Vision, and Graphics, pp. 59-77, 2003.
- A. Belaid, D. Boukerroui, Y. Maingourd and J. Lerallut, “Phase-Based Level Set Segmentation of Ultrasound Images”, IEEE Transactions on Information Technology in Biomedicine, Vol. 15, No. 1, pp. 138-147, 2011.
- V. Estellers, D. Zosso, X. Bresson and J. Thiran, “Harmonic Active Contours”, IEEE Transactions on Image Processing, Vol. 23, No. 1, pp. 69-82, 2014.
- P. Smereka, “Semi-Implicit Level Set Methods for Curvature and Surface Diffusion Motion”, Journal of Scientific Computing, Vol. 19, pp. 439-456, 2003.
- J. A. Sethian, “Approximation Schemes for Level Set Methods”, Cambridge Press, 1996.
- S. Osher and R. Fedkiw, “Level Set Methods and Dynamic Implicit Surfaces”, Springer, 2003.
- Kunal N. Chaudhury and K.R. Ramakrishnan, “Stability and Convergence of the Level Set Method in Computer Vision”, Pattern Recognition Letters, Vol. 28, pp. 884-893, 2007.
- T. Mendona, P.M. Ferreira, J. Marques, A.R.S. Marcal and J. Rozeira, “PH - A Dermoscopic Image Database for Research and Benchmarking”, Proceedings of IEEE International Conference on Engineering in Medicine and Biology Society, pp. 1-7, 2013.
- Ming Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Philip H. S. Torr and Shi-Min Hu, “Global Contrast based Salient Region Detection”, IEEE Transactions in Pattern Analysis and Machine Intelligence, Vol. 37, No. 3, pp. 569-582, 2015.
- Sharon Alpert, Meirav Galun, Ronen Basri and Achi Brandt, “Image Segmentation by Probabilistic Bottom-Up Aggregation and Cue Integration”, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1-12, 2007.
![](https://i-scholar.in/public/site/images/abstractview.png)
Abstract Views: 254
![](https://i-scholar.in/public/site/images/pdfview.png)
PDF Views: 1