Feature fusion and non-negative matrix factorization based active contours for texture segmentation
•Comprehensive feature fusion strategy via Gabor features and Local Variation Degree of intensity (LVD).•Effective energy functional via Non-negative Matrix Factorization (NMF).•Convex optimization strategy for robust results against different initializations.•Competitive results on the images with...
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| Published in | Signal processing Vol. 159; pp. 104 - 118 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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Elsevier B.V
01.06.2019
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| Abstract | •Comprehensive feature fusion strategy via Gabor features and Local Variation Degree of intensity (LVD).•Effective energy functional via Non-negative Matrix Factorization (NMF).•Convex optimization strategy for robust results against different initializations.•Competitive results on the images with noise and complex textures.
This paper presents a robust and convex active contour model for texture segmentation. Firstly, to achieve more comprehensive feature description, we compute a set of feature maps by combining local variation degree (LVD) of intensity and Gabor features. This feature fusion improves the separability between sub-regions and the robustness against complex textures. Upon these feature maps, we compute local histograms over fixed-size windows to describe the local structures formed by feature values. For each pixel, its feature vector is defined as the concatenation of all computed histograms. Secondly, to localize region boundaries more accurately, we formulate the proposed energy functional via Non-negative Matrix Factorization (NMF), which encourages each pixel to fall into the sub-region that has the largest coverage area in its neighborhood. Finally, the functional is explored further using convex optimization theory. Our segmentation results are therefore insensitive to different initial contours. The experiments performed on synthetic images, histology images and natural images demonstrate that our approach can obtain high-quality object boundaries in the presence of image noise and cluttered scenes. |
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| AbstractList | •Comprehensive feature fusion strategy via Gabor features and Local Variation Degree of intensity (LVD).•Effective energy functional via Non-negative Matrix Factorization (NMF).•Convex optimization strategy for robust results against different initializations.•Competitive results on the images with noise and complex textures.
This paper presents a robust and convex active contour model for texture segmentation. Firstly, to achieve more comprehensive feature description, we compute a set of feature maps by combining local variation degree (LVD) of intensity and Gabor features. This feature fusion improves the separability between sub-regions and the robustness against complex textures. Upon these feature maps, we compute local histograms over fixed-size windows to describe the local structures formed by feature values. For each pixel, its feature vector is defined as the concatenation of all computed histograms. Secondly, to localize region boundaries more accurately, we formulate the proposed energy functional via Non-negative Matrix Factorization (NMF), which encourages each pixel to fall into the sub-region that has the largest coverage area in its neighborhood. Finally, the functional is explored further using convex optimization theory. Our segmentation results are therefore insensitive to different initial contours. The experiments performed on synthetic images, histology images and natural images demonstrate that our approach can obtain high-quality object boundaries in the presence of image noise and cluttered scenes. |
| Author | Fang, Bin Chen, Hengxin Zheng, Shenhai Gao, Mingqi |
| Author_xml | – sequence: 1 givenname: Mingqi surname: Gao fullname: Gao, Mingqi organization: College of Computer Science, Chongqing University, Chongqing, China – sequence: 2 givenname: Hengxin surname: Chen fullname: Chen, Hengxin email: chenhengxin@cqu.edu.cn organization: College of Computer Science, Chongqing University, Chongqing, China – sequence: 3 givenname: Shenhai surname: Zheng fullname: Zheng, Shenhai organization: College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China – sequence: 4 givenname: Bin surname: Fang fullname: Fang, Bin organization: College of Computer Science, Chongqing University, Chongqing, China |
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| Cites_doi | 10.1007/BF01236935 10.1109/TIP.2013.2295752 10.1109/TIP.2014.2353814 10.1109/TCYB.2016.2577718 10.1023/A:1007979827043 10.1109/83.902291 10.1109/83.661186 10.1016/0021-9991(88)90002-2 10.1137/040615286 10.1109/TIP.2018.2806201 10.1109/TIP.2018.2848471 10.1016/j.neucom.2014.04.085 10.1109/TIP.2014.2372615 10.1016/j.sigpro.2016.06.013 10.1109/TCYB.2015.2409119 10.1016/j.cviu.2014.04.010 10.1016/j.patcog.2017.08.011 10.1109/TIP.2013.2263147 10.1007/BF00133570 10.1016/j.patcog.2014.10.018 10.1109/TIP.2006.871133 10.1007/s11263-009-0234-0 10.1109/TIP.2018.2792904 10.1109/TIP.2010.2069690 10.1109/TCYB.2014.2326059 10.1049/iet-ipr.2017.1144 10.1109/TPAMI.2010.161 10.1109/TIP.2015.2446948 10.1109/TIP.2016.2598653 10.1002/env.3170050203 10.1109/TCYB.2016.2585355 10.1016/j.patcog.2015.01.001 10.1016/j.sigpro.2009.03.014 10.1109/TIP.2014.2307475 10.1109/TIP.2008.2002304 10.1109/42.141646 10.1016/j.patcog.2015.03.001 10.1007/s11263-006-8711-1 10.1016/j.sigpro.2018.02.025 10.1109/TPAMI.2010.83 10.1109/TIP.2013.2274385 10.1007/s11042-018-5777-z 10.1007/s10851-007-0002-0 10.1016/j.patcog.2016.01.021 10.1016/j.patrec.2008.02.013 |
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| References | Mabood, Ali, Badshah, Chen, Khan (bib0022) 2016; 55 Li, Xu, Gui, Fox (bib0004) 2005 You, Guo, Yu, Li, Príncipe, Tao (bib0045) 2016; 25 Li, Kao, Gore, Ding (bib0008) 2008; 17 Ni, Bresson, Chan, Esedoglu (bib0028) 2009; 84 Li, Xu, Gui, Fox (bib0005) 2010; 19 Lui, Scharfenberger, Fergani, Wong, Clausi (bib0031) 2014; 23 Bresson, Esedoglu, Vandergheynst, Thiran, Osher (bib0054) 2007; 28 Ozolek, Castro (bib0049) 2011 Xu, Prince (bib0002) 1998; 7 Wang, Chen, Shi, Chang, Chan, Pu, Yang (bib0014) 2018; 149 Cremers, Rousson, Deriche (bib0017) 2007; 72 Li, Cui, Dong (bib0040) 2017; 9 Chen, Li, Pan, Xu (bib0038) 2018; 32 Zhao, Qin, Wang (bib0025) 2018; 77 Zheng, Fang, Li, Gao, Chen, Peng (bib0013) 2018; 73 Huang, Zhu, Wang, Chen (bib0047) 2014; 23 Min, Jia, Wang, Zhao, Hu, Luo, Xue, Lu (bib0027) 2015; 48 Zhang, Zhang, Lam, Zhang (bib0011) 2016; 46 Dong, Tao, Li (bib0041) 2015; 7 Gao, Bouix, Shenton, Tannenbaum (bib0030) 2013; 22 Chen, You, Zhong, Li, Tao (bib0046) 2017; 47 Alpert, Galun, Basri, Brandt (bib0056) 2007 Wang, Chan (bib0029) 2013; 22 Liu, Liu, Xing (bib0016) 2017; 130 Paatero, Tapper (bib0043) 1994; 5 Gerig, Kübler, Kikinis, Jolesz (bib0048) 1992; 11 Moreno, Prasath, Proença, Palaniappan (bib0055) 2014; 125 Min, Jia, Zhao, Zuo, Ling, Luo (bib0012) 2018; 27 Wang, He, Mishra, Li (bib0009) 2009; 89 Rousson, Brox, Deriche (bib0021) 2003 Zhu, You, Chen, Tao, Ou, Jiang, Zou (bib0044) 2015; 48 Savelonas, Iakovidis, Maroulis (bib0023) 2008; 29 Sagiv, Sochen, Zeevi (bib0019) 2006; 15 Caselles, Kimmel, Sapiro (bib0003) 1997; 22 Chan, Esedoglu, Nikolova (bib0052) 2006; 66 Chan, Vese (bib0007) 2001; 10 Wu, Yu (bib0020) 2018; 12 Peng, Zhang, Mou, Yang (bib0051) 2016; PP Li, Cui, Dong (bib0035) 2018; 9 Luo, Tong, Chen (bib0015) 2018; 27 Dong, Tao, Li, Ma, Pu (bib0042) 2015; 45 Yang, Gao, Tao, Li, Li (bib0010) 2015; 24 Arbelaez, Maire, Fowlkes, Malik (bib0050) 2011; 33 Yuan, Wang, Cheriyadat (bib0037) 2015; 24 Kass, Witkin, Terzopoulos (bib0001) 1988; 1 Sandberg, Chan, Vese (bib0018) 2004 Osher, Sethian (bib0034) 1988; 79 Wu, Gan, Lin, Zhang, Chang (bib0024) 2015; 151 Li, Cui, Dong (bib0039) 2017; 47 Fleming, Rishel (bib0057) 1960; 11 Dai, Ding, Yang (bib0026) 2015; 48 Mishra, Fieguth, Clausi (bib0006) 2011; 33 Kiechle, Storath, Weinmann, Kleinsteuber (bib0032) 2018; 27 Attouch, Buttazzo, Michaille (bib0053) 2014; vol. 17 SedlÃ!‘k, MorÃ!‘vek (bib0033) 1989; 42 McCann, Mixon, Fickus, Castro, Ozolek, Kovacevic (bib0036) 2014; 23 Wang (10.1016/j.sigpro.2019.01.021_bib0014) 2018; 149 Sagiv (10.1016/j.sigpro.2019.01.021_bib0019) 2006; 15 Cremers (10.1016/j.sigpro.2019.01.021_bib0017) 2007; 72 Min (10.1016/j.sigpro.2019.01.021_bib0012) 2018; 27 Bresson (10.1016/j.sigpro.2019.01.021_bib0054) 2007; 28 Wang (10.1016/j.sigpro.2019.01.021_bib0009) 2009; 89 Attouch (10.1016/j.sigpro.2019.01.021_bib0053) 2014; vol. 17 Gao (10.1016/j.sigpro.2019.01.021_bib0030) 2013; 22 Mabood (10.1016/j.sigpro.2019.01.021_bib0022) 2016; 55 Huang (10.1016/j.sigpro.2019.01.021_bib0047) 2014; 23 Caselles (10.1016/j.sigpro.2019.01.021_bib0003) 1997; 22 Savelonas (10.1016/j.sigpro.2019.01.021_bib0023) 2008; 29 Sandberg (10.1016/j.sigpro.2019.01.021_bib0018) 2004 Zhao (10.1016/j.sigpro.2019.01.021_bib0025) 2018; 77 Peng (10.1016/j.sigpro.2019.01.021_sbref0051) 2016; PP Li (10.1016/j.sigpro.2019.01.021_bib0008) 2008; 17 Paatero (10.1016/j.sigpro.2019.01.021_bib0043) 1994; 5 Dai (10.1016/j.sigpro.2019.01.021_bib0026) 2015; 48 Chen (10.1016/j.sigpro.2019.01.021_bib0038) 2018; 32 Lui (10.1016/j.sigpro.2019.01.021_bib0031) 2014; 23 Li (10.1016/j.sigpro.2019.01.021_bib0039) 2017; 47 Gerig (10.1016/j.sigpro.2019.01.021_bib0048) 1992; 11 Ni (10.1016/j.sigpro.2019.01.021_bib0028) 2009; 84 Dong (10.1016/j.sigpro.2019.01.021_bib0041) 2015; 7 Zhang (10.1016/j.sigpro.2019.01.021_bib0011) 2016; 46 McCann (10.1016/j.sigpro.2019.01.021_bib0036) 2014; 23 Zheng (10.1016/j.sigpro.2019.01.021_bib0013) 2018; 73 Kass (10.1016/j.sigpro.2019.01.021_bib0001) 1988; 1 Chan (10.1016/j.sigpro.2019.01.021_bib0052) 2006; 66 Luo (10.1016/j.sigpro.2019.01.021_bib0015) 2018; 27 Chan (10.1016/j.sigpro.2019.01.021_bib0007) 2001; 10 Mishra (10.1016/j.sigpro.2019.01.021_bib0006) 2011; 33 Li (10.1016/j.sigpro.2019.01.021_bib0004) 2005 You (10.1016/j.sigpro.2019.01.021_bib0045) 2016; 25 Yuan (10.1016/j.sigpro.2019.01.021_bib0037) 2015; 24 Liu (10.1016/j.sigpro.2019.01.021_bib0016) 2017; 130 Chen (10.1016/j.sigpro.2019.01.021_bib0046) 2017; 47 Dong (10.1016/j.sigpro.2019.01.021_bib0042) 2015; 45 Li (10.1016/j.sigpro.2019.01.021_sbref0040) 2017; 9 Zhu (10.1016/j.sigpro.2019.01.021_bib0044) 2015; 48 Kiechle (10.1016/j.sigpro.2019.01.021_bib0032) 2018; 27 Xu (10.1016/j.sigpro.2019.01.021_bib0002) 1998; 7 Moreno (10.1016/j.sigpro.2019.01.021_bib0055) 2014; 125 Li (10.1016/j.sigpro.2019.01.021_bib0005) 2010; 19 Wu (10.1016/j.sigpro.2019.01.021_bib0020) 2018; 12 Rousson (10.1016/j.sigpro.2019.01.021_bib0021) 2003 Min (10.1016/j.sigpro.2019.01.021_bib0027) 2015; 48 Wang (10.1016/j.sigpro.2019.01.021_bib0029) 2013; 22 SedlÃ!‘k (10.1016/j.sigpro.2019.01.021_bib0033) 1989; 42 Osher (10.1016/j.sigpro.2019.01.021_bib0034) 1988; 79 Li (10.1016/j.sigpro.2019.01.021_bib0035) 2018; 9 Yang (10.1016/j.sigpro.2019.01.021_bib0010) 2015; 24 Wu (10.1016/j.sigpro.2019.01.021_bib0024) 2015; 151 Arbelaez (10.1016/j.sigpro.2019.01.021_bib0050) 2011; 33 Ozolek (10.1016/j.sigpro.2019.01.021_bib0049) 2011 Alpert (10.1016/j.sigpro.2019.01.021_bib0056) 2007 Fleming (10.1016/j.sigpro.2019.01.021_bib0057) 1960; 11 |
| References_xml | – volume: 46 start-page: 546 year: 2016 end-page: 557 ident: bib0011 article-title: A level set approach to image segmentation with intensity inhomogeneity publication-title: IEEE Trans. Cybern. – volume: 32 start-page: 1 year: 2018 end-page: 32 ident: bib0038 article-title: Fast non-negative matrix factorizations for face recognition publication-title: IJPRAI – volume: 29 start-page: 1404 year: 2008 end-page: 1415 ident: bib0023 article-title: LBP-guided active contours publication-title: Pattern Recognit. Lett. – volume: 33 start-page: 310 year: 2011 end-page: 324 ident: bib0006 article-title: Decoupled active contour (DAC) for boundary detection publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 7 start-page: 359 year: 1998 end-page: 369 ident: bib0002 article-title: Snakes, shapes, and gradient vector flow publication-title: IEEE Trans. Image Process. – volume: 125 start-page: 237 year: 2014 end-page: 250 ident: bib0055 article-title: Fast and globally convex multiphase active contours for brain MRI segmentation publication-title: Comput. Vision Image Understand. – volume: 73 start-page: 144 year: 2018 end-page: 157 ident: bib0013 article-title: B-spline based globally optimal segmentation combining low-level and high-level information publication-title: Pattern Recognit. – volume: 27 start-page: 1994 year: 2018 end-page: 2007 ident: bib0032 article-title: Model-based learning of local image features for unsupervised texture segmentation publication-title: IEEE Trans. Image Process. – volume: 149 start-page: 27 year: 2018 end-page: 35 ident: bib0014 article-title: Active contours driven by edge entropy fitting energy for image segmentation publication-title: Sig. Process. – volume: 72 start-page: 195 year: 2007 end-page: 215 ident: bib0017 article-title: A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape publication-title: Int. J. Comput. Vis. – volume: 7 start-page: 4:1 year: 2015 end-page: 4:21 ident: bib0041 article-title: Nonnegative multiresolution representation-based texture image classification publication-title: ACM TIST – volume: 89 start-page: 2435 year: 2009 end-page: 2447 ident: bib0009 article-title: Active contours driven by local Gaussian distribution fitting energy publication-title: Sig. Process. – year: 2011 ident: bib0049 article-title: Teratomas Derived from Embryonic Stem Cells as Models for Embryonic Development, Disease, and Tumorigenesis – volume: 84 start-page: 97 year: 2009 end-page: 111 ident: bib0028 article-title: Local histogram based segmentation using the wasserstein distance publication-title: Int. J. Comput. Vis. – volume: 48 start-page: 2592 year: 2015 end-page: 2608 ident: bib0044 article-title: An adaptive hybrid pattern for noise-robust texture analysis publication-title: Pattern Recognit. – volume: 77 start-page: 24537 year: 2018 end-page: 24564 ident: bib0025 article-title: Interactive segmentation of texture image based on active contour model with local inverse difference moment feature publication-title: Multimed. Tools Appl. – volume: vol. 17 year: 2014 ident: bib0053 article-title: Variational Analysis in Sobolev and BV Spaces - Applications to PDEs and Optimization publication-title: MPS-SIAM Series on Optimization – volume: 11 start-page: 221 year: 1992 end-page: 232 ident: bib0048 article-title: Nonlinear anisotropic filtering of MRI data publication-title: IEEE Trans. Med. Imaging – volume: 33 start-page: 898 year: 2011 end-page: 916 ident: bib0050 article-title: Contour detection and hierarchical image segmentation publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 9 year: 2017 ident: bib0040 article-title: Refined-graph regularization-based nonnegative matrix factorization publication-title: ACM TIST – volume: 27 start-page: 2560 year: 2018 end-page: 2574 ident: bib0015 article-title: A multi-region segmentation method for SAR images based on the multi-texture model with level sets publication-title: IEEE Trans. Image Process. – volume: 28 start-page: 151 year: 2007 end-page: 167 ident: bib0054 article-title: Fast global minimization of the active contour/snake model publication-title: J. Math. Imaging Vis. – volume: 66 start-page: 1632 year: 2006 end-page: 1648 ident: bib0052 article-title: Algorithms for finding global minimizers of image segmentation and denoising models publication-title: SIAM J. Appl. Math. – volume: 23 start-page: 4680 year: 2014 end-page: 4695 ident: bib0047 article-title: HSOG: A novel local image descriptor based on histograms of the second-order gradients publication-title: IEEE Trans. Image Process. – volume: 55 start-page: 87 year: 2016 end-page: 99 ident: bib0022 article-title: Active contours textural and inhomogeneous object extraction publication-title: Pattern Recognit. – volume: 45 start-page: 358 year: 2015 end-page: 369 ident: bib0042 article-title: Texture classification and retrieval using shearlets and linear regression publication-title: IEEE Trans. Cybern. – volume: 17 start-page: 1940 year: 2008 end-page: 1949 ident: bib0008 article-title: Minimization of region-scalable fitting energy for image segmentation publication-title: IEEE Trans. Image Process. – start-page: 430 year: 2005 end-page: 436 ident: bib0004 article-title: Level set evolution without re-initialization: a new variational formulation publication-title: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 20–26 June 2005, San Diego, CA, USA – volume: 48 start-page: 2513 year: 2015 end-page: 2529 ident: bib0026 article-title: Inhomogeneity-embedded active contour for natural image segmentation publication-title: Pattern Recognit. – volume: 47 start-page: 3840 year: 2017 end-page: 3853 ident: bib0039 article-title: Graph regularized non-negative low-rank matrix factorization for image clustering publication-title: IEEE Trans. Cybern. – volume: 27 start-page: 5016 year: 2018 end-page: 5031 ident: bib0012 article-title: Late: a level-set method based on local approximation of taylor expansion for segmenting intensity inhomogeneous images publication-title: IEEE Trans. Image Process. – year: 2007 ident: bib0056 article-title: Image segmentation by probabilistic bottom-up aggregation and cue integration publication-title: 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 18–23 June 2007, Minneapolis, Minnesota, USA – volume: 42 start-page: 577?685 year: 1989 ident: bib0033 article-title: Optimal approximations by piecewise smooth functions and associated variational problems publication-title: Commun. Pure Appl. Math. – volume: 22 start-page: 3866 year: 2013 end-page: 3878 ident: bib0030 article-title: Sparse texture active contour publication-title: IEEE Trans. Image Process. – volume: 23 start-page: 855 year: 2014 end-page: 869 ident: bib0031 article-title: Enhanced decoupled active contour using structural and textural variation energy functionals publication-title: IEEE Trans. Image Process. – volume: 5 start-page: 111 year: 1994 end-page: 126 ident: bib0043 article-title: Positive matrix factorization: a nonnegative factor model with optimal utilization of error estimates of data values publication-title: Environmetrics – volume: 9 start-page: 65:1 year: 2018 end-page: 65:24 ident: bib0035 article-title: Discriminative and orthogonal subspace constraints-based nonnegative matrix factorization publication-title: ACM TIST – volume: 22 start-page: 61 year: 1997 end-page: 79 ident: bib0003 article-title: Geodesic active contours publication-title: Int. J. Comput. Vis. – volume: 19 start-page: 3243 year: 2010 end-page: 3254 ident: bib0005 article-title: Distance regularized level set evolution and its application to image segmentation publication-title: IEEE Trans. Image Process. – volume: 15 start-page: 1633 year: 2006 end-page: 1646 ident: bib0019 article-title: Integrated active contours for texture segmentation publication-title: IEEE Trans. Image Process. – volume: 48 start-page: 1547 year: 2015 end-page: 1562 ident: bib0027 article-title: An intensity-texture model based level set method for image segmentation publication-title: Pattern Recognit. – start-page: 699 year: 2003 end-page: 706 ident: bib0021 article-title: Active unsupervised texture segmentation on a diffusion based feature space publication-title: 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2003), 16–22 June 2003, Madison, WI, USA – volume: 1 start-page: 321 year: 1988 end-page: 331 ident: bib0001 article-title: Snakes: active contour models publication-title: Int. J. Comput. Vis. – volume: 130 start-page: 12 year: 2017 end-page: 21 ident: bib0016 article-title: An improved edge-based level set method combining local regional fitting information for noisy image segmentation publication-title: Sig. Process. – volume: 22 start-page: 4473 year: 2013 end-page: 4485 ident: bib0029 article-title: Incorporating patch subspace model in Mumford-Shah type active contours publication-title: IEEE Trans. Image Process. – volume: 151 start-page: 1133 year: 2015 end-page: 1141 ident: bib0024 article-title: An active contour model based on fused texture features for image segmentation publication-title: Neurocomputing – volume: 10 start-page: 266 year: 2001 end-page: 277 ident: bib0007 article-title: Active contours without edges publication-title: IEEE Trans. Image Process. – volume: 12 start-page: 1131 year: 2018 end-page: 1141 ident: bib0020 article-title: Automatic object extraction from images using deep neural networks and the level-set method publication-title: IET Image Process. – volume: 47 start-page: 3706 year: 2017 end-page: 3718 ident: bib0046 article-title: Dynamically modulated mask sparse tracking publication-title: IEEE Trans. Cybern. – volume: 23 start-page: 2033 year: 2014 end-page: 2046 ident: bib0036 article-title: Images as occlusions of textures: a framework for segmentation publication-title: IEEE Trans. Image Process. – volume: 24 start-page: 9 year: 2015 end-page: 21 ident: bib0010 article-title: An efficient MRF embedded level set method for image segmentation publication-title: IEEE Trans. Image Process. – volume: 79 start-page: 12 year: 1988 end-page: 49 ident: bib0034 article-title: Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations publication-title: J. Comput. Phys. – volume: PP year: 2016 ident: bib0051 article-title: Evaluation of segmentation quality via adaptive composition of reference segmentations. publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 11 start-page: 218 year: 1960 end-page: 222 ident: bib0057 article-title: An integral formula for total gradient variation publication-title: Arch. Math. – volume: 25 start-page: 4782 year: 2016 end-page: 4795 ident: bib0045 article-title: Kernel learning for dynamic texture synthesis publication-title: IEEE Trans. Image Process. – year: 2004 ident: bib0018 article-title: A Level-Set and Gabor-Based Active Contour Algorithm for Segmenting Textured Images publication-title: Ucla Department of Mathematics Cam Report – volume: 24 start-page: 3488 year: 2015 end-page: 3497 ident: bib0037 article-title: Factorization-based texture segmentation publication-title: IEEE Trans. Image Process. – volume: 11 start-page: 218 issue: 1 year: 1960 ident: 10.1016/j.sigpro.2019.01.021_bib0057 article-title: An integral formula for total gradient variation publication-title: Arch. Math. doi: 10.1007/BF01236935 – volume: 23 start-page: 855 issue: 2 year: 2014 ident: 10.1016/j.sigpro.2019.01.021_bib0031 article-title: Enhanced decoupled active contour using structural and textural variation energy functionals publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2013.2295752 – volume: 23 start-page: 4680 issue: 11 year: 2014 ident: 10.1016/j.sigpro.2019.01.021_bib0047 article-title: HSOG: A novel local image descriptor based on histograms of the second-order gradients publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2014.2353814 – volume: 47 start-page: 3706 issue: 11 year: 2017 ident: 10.1016/j.sigpro.2019.01.021_bib0046 article-title: Dynamically modulated mask sparse tracking publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2577718 – volume: 22 start-page: 61 issue: 1 year: 1997 ident: 10.1016/j.sigpro.2019.01.021_bib0003 article-title: Geodesic active contours publication-title: Int. J. Comput. Vis. doi: 10.1023/A:1007979827043 – volume: 10 start-page: 266 issue: 2 year: 2001 ident: 10.1016/j.sigpro.2019.01.021_bib0007 article-title: Active contours without edges publication-title: IEEE Trans. Image Process. doi: 10.1109/83.902291 – volume: 9 issue: 1 year: 2017 ident: 10.1016/j.sigpro.2019.01.021_sbref0040 article-title: Refined-graph regularization-based nonnegative matrix factorization publication-title: ACM TIST – volume: 7 start-page: 359 issue: 3 year: 1998 ident: 10.1016/j.sigpro.2019.01.021_bib0002 article-title: Snakes, shapes, and gradient vector flow publication-title: IEEE Trans. Image Process. doi: 10.1109/83.661186 – volume: 79 start-page: 12 issue: 1 year: 1988 ident: 10.1016/j.sigpro.2019.01.021_bib0034 article-title: Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations publication-title: J. Comput. Phys. doi: 10.1016/0021-9991(88)90002-2 – volume: 66 start-page: 1632 issue: 5 year: 2006 ident: 10.1016/j.sigpro.2019.01.021_bib0052 article-title: Algorithms for finding global minimizers of image segmentation and denoising models publication-title: SIAM J. Appl. Math. doi: 10.1137/040615286 – volume: 27 start-page: 2560 issue: 5 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0015 article-title: A multi-region segmentation method for SAR images based on the multi-texture model with level sets publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2018.2806201 – volume: 27 start-page: 5016 issue: 10 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0012 article-title: Late: a level-set method based on local approximation of taylor expansion for segmenting intensity inhomogeneous images publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2018.2848471 – volume: 42 start-page: 577?685 issue: 5 year: 1989 ident: 10.1016/j.sigpro.2019.01.021_bib0033 article-title: Optimal approximations by piecewise smooth functions and associated variational problems publication-title: Commun. Pure Appl. Math. – volume: 151 start-page: 1133 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0024 article-title: An active contour model based on fused texture features for image segmentation publication-title: Neurocomputing doi: 10.1016/j.neucom.2014.04.085 – volume: 24 start-page: 9 issue: 1 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0010 article-title: An efficient MRF embedded level set method for image segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2014.2372615 – volume: 130 start-page: 12 year: 2017 ident: 10.1016/j.sigpro.2019.01.021_bib0016 article-title: An improved edge-based level set method combining local regional fitting information for noisy image segmentation publication-title: Sig. Process. doi: 10.1016/j.sigpro.2016.06.013 – volume: 46 start-page: 546 issue: 2 year: 2016 ident: 10.1016/j.sigpro.2019.01.021_bib0011 article-title: A level set approach to image segmentation with intensity inhomogeneity publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2015.2409119 – volume: 7 start-page: 4:1 issue: 1 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0041 article-title: Nonnegative multiresolution representation-based texture image classification publication-title: ACM TIST – volume: 125 start-page: 237 year: 2014 ident: 10.1016/j.sigpro.2019.01.021_bib0055 article-title: Fast and globally convex multiphase active contours for brain MRI segmentation publication-title: Comput. Vision Image Understand. doi: 10.1016/j.cviu.2014.04.010 – volume: 73 start-page: 144 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0013 article-title: B-spline based globally optimal segmentation combining low-level and high-level information publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2017.08.011 – volume: 22 start-page: 3866 issue: 10 year: 2013 ident: 10.1016/j.sigpro.2019.01.021_bib0030 article-title: Sparse texture active contour publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2013.2263147 – volume: 1 start-page: 321 issue: 4 year: 1988 ident: 10.1016/j.sigpro.2019.01.021_bib0001 article-title: Snakes: active contour models publication-title: Int. J. Comput. Vis. doi: 10.1007/BF00133570 – volume: 48 start-page: 1547 issue: 4 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0027 article-title: An intensity-texture model based level set method for image segmentation publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2014.10.018 – volume: 15 start-page: 1633 issue: 6 year: 2006 ident: 10.1016/j.sigpro.2019.01.021_bib0019 article-title: Integrated active contours for texture segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2006.871133 – year: 2004 ident: 10.1016/j.sigpro.2019.01.021_bib0018 article-title: A Level-Set and Gabor-Based Active Contour Algorithm for Segmenting Textured Images – volume: 84 start-page: 97 issue: 1 year: 2009 ident: 10.1016/j.sigpro.2019.01.021_bib0028 article-title: Local histogram based segmentation using the wasserstein distance publication-title: Int. J. Comput. Vis. doi: 10.1007/s11263-009-0234-0 – volume: 27 start-page: 1994 issue: 4 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0032 article-title: Model-based learning of local image features for unsupervised texture segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2018.2792904 – volume: vol. 17 year: 2014 ident: 10.1016/j.sigpro.2019.01.021_bib0053 article-title: Variational Analysis in Sobolev and BV Spaces - Applications to PDEs and Optimization – volume: 19 start-page: 3243 issue: 12 year: 2010 ident: 10.1016/j.sigpro.2019.01.021_bib0005 article-title: Distance regularized level set evolution and its application to image segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2010.2069690 – volume: 45 start-page: 358 issue: 3 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0042 article-title: Texture classification and retrieval using shearlets and linear regression publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2014.2326059 – volume: 12 start-page: 1131 issue: 7 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0020 article-title: Automatic object extraction from images using deep neural networks and the level-set method publication-title: IET Image Process. doi: 10.1049/iet-ipr.2017.1144 – volume: 33 start-page: 898 issue: 5 year: 2011 ident: 10.1016/j.sigpro.2019.01.021_bib0050 article-title: Contour detection and hierarchical image segmentation publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2010.161 – volume: 24 start-page: 3488 issue: 11 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0037 article-title: Factorization-based texture segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2015.2446948 – volume: 25 start-page: 4782 issue: 10 year: 2016 ident: 10.1016/j.sigpro.2019.01.021_bib0045 article-title: Kernel learning for dynamic texture synthesis publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2016.2598653 – volume: 5 start-page: 111 issue: 2 year: 1994 ident: 10.1016/j.sigpro.2019.01.021_bib0043 article-title: Positive matrix factorization: a nonnegative factor model with optimal utilization of error estimates of data values publication-title: Environmetrics doi: 10.1002/env.3170050203 – volume: 32 start-page: 1 issue: 4 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0038 article-title: Fast non-negative matrix factorizations for face recognition publication-title: IJPRAI – volume: 47 start-page: 3840 issue: 11 year: 2017 ident: 10.1016/j.sigpro.2019.01.021_bib0039 article-title: Graph regularized non-negative low-rank matrix factorization for image clustering publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2585355 – start-page: 699 year: 2003 ident: 10.1016/j.sigpro.2019.01.021_bib0021 article-title: Active unsupervised texture segmentation on a diffusion based feature space – year: 2011 ident: 10.1016/j.sigpro.2019.01.021_bib0049 – volume: 48 start-page: 2592 issue: 8 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0044 article-title: An adaptive hybrid pattern for noise-robust texture analysis publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.01.001 – volume: 89 start-page: 2435 issue: 12 year: 2009 ident: 10.1016/j.sigpro.2019.01.021_bib0009 article-title: Active contours driven by local Gaussian distribution fitting energy publication-title: Sig. Process. doi: 10.1016/j.sigpro.2009.03.014 – volume: 23 start-page: 2033 issue: 5 year: 2014 ident: 10.1016/j.sigpro.2019.01.021_bib0036 article-title: Images as occlusions of textures: a framework for segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2014.2307475 – volume: 17 start-page: 1940 issue: 10 year: 2008 ident: 10.1016/j.sigpro.2019.01.021_bib0008 article-title: Minimization of region-scalable fitting energy for image segmentation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2008.2002304 – volume: PP issue: 99 year: 2016 ident: 10.1016/j.sigpro.2019.01.021_sbref0051 article-title: Evaluation of segmentation quality via adaptive composition of reference segmentations. publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 11 start-page: 221 issue: 2 year: 1992 ident: 10.1016/j.sigpro.2019.01.021_bib0048 article-title: Nonlinear anisotropic filtering of MRI data publication-title: IEEE Trans. Med. Imaging doi: 10.1109/42.141646 – volume: 48 start-page: 2513 issue: 8 year: 2015 ident: 10.1016/j.sigpro.2019.01.021_bib0026 article-title: Inhomogeneity-embedded active contour for natural image segmentation publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.03.001 – volume: 72 start-page: 195 issue: 2 year: 2007 ident: 10.1016/j.sigpro.2019.01.021_bib0017 article-title: A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape publication-title: Int. J. Comput. Vis. doi: 10.1007/s11263-006-8711-1 – volume: 149 start-page: 27 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0014 article-title: Active contours driven by edge entropy fitting energy for image segmentation publication-title: Sig. Process. doi: 10.1016/j.sigpro.2018.02.025 – volume: 33 start-page: 310 issue: 2 year: 2011 ident: 10.1016/j.sigpro.2019.01.021_bib0006 article-title: Decoupled active contour (DAC) for boundary detection publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/TPAMI.2010.83 – start-page: 430 year: 2005 ident: 10.1016/j.sigpro.2019.01.021_bib0004 article-title: Level set evolution without re-initialization: a new variational formulation – volume: 22 start-page: 4473 issue: 11 year: 2013 ident: 10.1016/j.sigpro.2019.01.021_bib0029 article-title: Incorporating patch subspace model in Mumford-Shah type active contours publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2013.2274385 – volume: 77 start-page: 24537 issue: 18 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0025 article-title: Interactive segmentation of texture image based on active contour model with local inverse difference moment feature publication-title: Multimed. Tools Appl. doi: 10.1007/s11042-018-5777-z – volume: 28 start-page: 151 issue: 2 year: 2007 ident: 10.1016/j.sigpro.2019.01.021_bib0054 article-title: Fast global minimization of the active contour/snake model publication-title: J. Math. Imaging Vis. doi: 10.1007/s10851-007-0002-0 – year: 2007 ident: 10.1016/j.sigpro.2019.01.021_bib0056 article-title: Image segmentation by probabilistic bottom-up aggregation and cue integration – volume: 55 start-page: 87 year: 2016 ident: 10.1016/j.sigpro.2019.01.021_bib0022 article-title: Active contours textural and inhomogeneous object extraction publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.01.021 – volume: 29 start-page: 1404 issue: 9 year: 2008 ident: 10.1016/j.sigpro.2019.01.021_bib0023 article-title: LBP-guided active contours publication-title: Pattern Recognit. Lett. doi: 10.1016/j.patrec.2008.02.013 – volume: 9 start-page: 65:1 issue: 6 year: 2018 ident: 10.1016/j.sigpro.2019.01.021_bib0035 article-title: Discriminative and orthogonal subspace constraints-based nonnegative matrix factorization publication-title: ACM TIST |
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