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Volumn 30, Issue 12, 2008, Pages 2126-2139

IRGS: Image segmentation using edge penalties and region growing

Author keywords

Gaussian mixture; Hybrid region and edge; Markov random field (MRF); Region Adjacency Graph (RAG); Region growing

Indexed keywords

DIGITAL IMAGE STORAGE; HIDDEN MARKOV MODELS; IMAGE ENHANCEMENT; IMAGE PROCESSING; IMAGE SEGMENTATION; IMAGING SYSTEMS; INFORMATION THEORY; KNOWLEDGE REPRESENTATION; LAWS AND LEGISLATION; PROBABILITY DENSITY FUNCTION; RADAR; STRUCTURAL FRAMES; SYNTHETIC APERTURE RADAR; SYNTHETIC APERTURES; TARGET DRONES;

EID: 56549121535     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.15     Document Type: Article
Times cited : (203)

References (49)
  • 1
    • 0018306059 scopus 로고
    • A Threshold Selection Method from Gray-Level Histograms
    • N. Otsu, "A Threshold Selection Method from Gray-Level Histograms," IEEE Trans. Systems, Man, and Cybernetics, vol. 9, pp. 62-66, 1979.
    • (1979) IEEE Trans. Systems, Man, and Cybernetics , vol.9 , pp. 62-66
    • Otsu, N.1
  • 4
    • 0034246174 scopus 로고    scopus 로고
    • Edgeflow: A Technique for Boundary Detection and Image Segmentation
    • W.Y. Ma and B.S. Manjunath, "Edgeflow: A Technique for Boundary Detection and Image Segmentation," IEEE Trans. Image Processing, vol. 9, no. 8, 2000.
    • (2000) IEEE Trans. Image Processing , vol.9 , Issue.8
    • Ma, W.Y.1    Manjunath, B.S.2
  • 6
    • 0026172104 scopus 로고
    • Watershed in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
    • June
    • L. Vincent and P. Soille, "Watershed in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 13, no. 6, pp. 583-598, June 1991.
    • (1991) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.13 , Issue.6 , pp. 583-598
    • Vincent, L.1    Soille, P.2
  • 11
    • 0036501532 scopus 로고    scopus 로고
    • A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations
    • J.A. Yezzi, A. Tsai, and A. Willsky, "A Fully Global Approach to Image Segmentation via Coupled Curve Evolution Equations," J. Visual Comm. and Image Representation, vol. 13, pp. 195-216, 2002.
    • (2002) J. Visual Comm. and Image Representation , vol.13 , pp. 195-216
    • Yezzi, J.A.1    Tsai, A.2    Willsky, A.3
  • 12
    • 0000013152 scopus 로고
    • On the Statistical Analysis of Dirty Pictures
    • J. Besag, "On the Statistical Analysis of Dirty Pictures," J. Royal Statistical Soc. B, vol. 48, no. 3, pp. 259-302, 1986.
    • (1986) J. Royal Statistical Soc. B , vol.48 , Issue.3 , pp. 259-302
    • Besag, J.1
  • 13
    • 0023123263 scopus 로고
    • Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random Fields
    • Jan
    • H. Derin and H. Elliott, "Modeling and Segmentation of Noisy and Textured Images Using Gibbs Random Fields," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 1, pp. 39-55, Jan. 1987.
    • (1987) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.9 , Issue.1 , pp. 39-55
    • Derin, H.1    Elliott, H.2
  • 14
    • 0021518209 scopus 로고
    • Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
    • S. Geman and D. Geman, "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 6, no. 6, pp. 721-741, 1984.
    • (1984) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.6 , Issue.6 , pp. 721-741
    • Geman, S.1    Geman, D.2
  • 16
    • 33646590894 scopus 로고    scopus 로고
    • Discriminative Random Fields
    • S. Kumar and M. Hebert, "Discriminative Random Fields," Int'l J. Computer Vision, vol. 68, no. 2, pp. 179-202, 2006.
    • (2006) Int'l J. Computer Vision , vol.68 , Issue.2 , pp. 179-202
    • Kumar, S.1    Hebert, M.2
  • 18
    • 44049114806 scopus 로고
    • Unsupervised Segmentation of Noisy and Textured Images Using Markov Random Fields
    • C.S. Won and H. Derin, "Unsupervised Segmentation of Noisy and Textured Images Using Markov Random Fields," CVGIP: Graphical Models and Image Processing, vol. 54, no. 4, pp. 308-328, 1992.
    • (1992) CVGIP: Graphical Models and Image Processing , vol.54 , Issue.4 , pp. 308-328
    • Won, C.S.1    Derin, H.2
  • 19
    • 36348963479 scopus 로고    scopus 로고
    • Combining Local and Global Features for Image Segmentation Using Iterative Classification and Region Merging
    • May
    • Q. Yu and D.A. Clausi, "Combining Local and Global Features for Image Segmentation Using Iterative Classification and Region Merging," Proc. Second Canadian Conf. Computer and Robot Vision, May 2005.
    • (2005) Proc. Second Canadian Conf. Computer and Robot Vision
    • Yu, Q.1    Clausi, D.A.2
  • 20
    • 0034442865 scopus 로고    scopus 로고
    • Joint Region Merging Criteria for Watershed-Based Image Segmentation
    • Sept
    • S.E. Hernandez and K.E. Barner, "Joint Region Merging Criteria for Watershed-Based Image Segmentation," Proc. Int'l Conf. Image Processing, vol. 2, pp. 108-111, Sept. 2000.
    • (2000) Proc. Int'l Conf. Image Processing , vol.2 , pp. 108-111
    • Hernandez, S.E.1    Barner, K.E.2
  • 21
  • 23
    • 12344323744 scopus 로고    scopus 로고
    • Unsupervised Image Segmentation Using a Simple MRF Model with a New Implementation Scheme
    • H. Deng and D.A. Clausi, "Unsupervised Image Segmentation Using a Simple MRF Model with a New Implementation Scheme," Pattern Recognition, vol. 37, no. 12, pp. 2323-2335, 2004.
    • (2004) Pattern Recognition , vol.37 , Issue.12 , pp. 2323-2335
    • Deng, H.1    Clausi, D.A.2
  • 24
    • 0036566199 scopus 로고    scopus 로고
    • Image Segmentation by Data-Driven Markov Chain Monte Carlo
    • May
    • Z. Tu and S.C. Zhu, "Image Segmentation by Data-Driven Markov Chain Monte Carlo," IEEE Trans. Pattern Analysis and Machine Intelligence vol. 24, no. 5, pp. 657-673, May 2002.
    • (2002) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.24 , Issue.5 , pp. 657-673
    • Tu, Z.1    Zhu, S.C.2
  • 25
    • 0032022414 scopus 로고    scopus 로고
    • Unsupervised Segmentation of Markov Random Field Modeled Textured Images Using Selectionist Relaxation
    • Mar
    • P. Andrey and P. Tarroux, "Unsupervised Segmentation of Markov Random Field Modeled Textured Images Using Selectionist Relaxation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 3, pp. 252-262, Mar. 1998.
    • (1998) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.20 , Issue.3 , pp. 252-262
    • Andrey, P.1    Tarroux, P.2
  • 27
    • 0026938712 scopus 로고
    • The Mean Field Theory in EM Procedures for Markov Random Fields
    • J. Zhang, "The Mean Field Theory in EM Procedures for Markov Random Fields," IEEE Trans. Signal Processing, vol. 40, no. 10, pp. 2570-2583, 1992.
    • (1992) IEEE Trans. Signal Processing , vol.40 , Issue.10 , pp. 2570-2583
    • Zhang, J.1
  • 28
    • 0028392841 scopus 로고
    • A Multiscale Random Field Model for Bayesian Image Segmentation
    • C. Bouman and M. Shapiro, "A Multiscale Random Field Model for Bayesian Image Segmentation," IEEE Trans. Image Processing, vol. 3, no. 2, 1994.
    • (1994) IEEE Trans. Image Processing , vol.3 , Issue.2
    • Bouman, C.1    Shapiro, M.2
  • 29
    • 0029732459 scopus 로고    scopus 로고
    • A Hierarchical Markov Random Field Model and Multitemperature Annealing for Parallel Image Classification
    • Z. Kato, M. Berthod, and J. Zerubia, "A Hierarchical Markov Random Field Model and Multitemperature Annealing for Parallel Image Classification," Graphic Models and Image Processing, vol. 58, no. 1, pp. 18-37, 1996.
    • (1996) Graphic Models and Image Processing , vol.58 , Issue.1 , pp. 18-37
    • Kato, Z.1    Berthod, M.2    Zerubia, J.3
  • 30
    • 0033878097 scopus 로고    scopus 로고
    • Discrete Markov Image Modeling and Inference on the Quadtree
    • J. Laferte, P. Perez, and F. Heitz, "Discrete Markov Image Modeling and Inference on the Quadtree," IEEE Trans. Image Processing, vol. 9, no. 3, 2000.
    • (2000) IEEE Trans. Image Processing , vol.9 , Issue.3
    • Laferte, J.1    Perez, P.2    Heitz, F.3
  • 31
    • 0037247155 scopus 로고    scopus 로고
    • A Class of Discrete Multiresolution Random Fields and Its Application to Image Segmentation
    • Jan
    • R. Wilson and C. Li, "A Class of Discrete Multiresolution Random Fields and Its Application to Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 1, pp. 42-56, Jan. 2002.
    • (2002) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.25 , Issue.1 , pp. 42-56
    • Wilson, R.1    Li, C.2
  • 32
    • 24344434731 scopus 로고    scopus 로고
    • Generalizing Swendsen-Wang to Sampling Arbitrary Posterior Probabilities
    • Aug
    • A. Barbu and S.C. Zhu, "Generalizing Swendsen-Wang to Sampling Arbitrary Posterior Probabilities," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 8, pp. 1239-1253, Aug. 2005.
    • (2005) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.27 , Issue.8 , pp. 1239-1253
    • Barbu, A.1    Zhu, S.C.2
  • 35
    • 0033730971 scopus 로고    scopus 로고
    • A Simple Unsupervised MRF Model Based Image Segmentation Approach
    • A. Sarkar, M.K. Biswas, and K.M.S. Sharma, "A Simple Unsupervised MRF Model Based Image Segmentation Approach," IEEE Trans. Image Processing, vol. 9, no. 5, pp. 801-812, 2000.
    • (2000) IEEE Trans. Image Processing , vol.9 , Issue.5 , pp. 801-812
    • Sarkar, A.1    Biswas, M.K.2    Sharma, K.M.S.3
  • 36
    • 0030247213 scopus 로고    scopus 로고
    • Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
    • Sept
    • S.C. Zhu and A. Yuille, "Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 9, pp. 884-900, Sept. 1996.
    • (1996) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.18 , Issue.9 , pp. 884-900
    • Zhu, S.C.1    Yuille, A.2
  • 38
    • 0002629270 scopus 로고
    • Maximum Likelihood from Incomplete Data via the EM Algorithm
    • A.P. Dempster, N.M. Laird, and D.B. Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," J. Royal Statistical Soc. B vol. 39, no. 1, pp. 1-38, 1977.
    • (1977) J. Royal Statistical Soc. B , vol.39 , Issue.1 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 39
    • 0026899931 scopus 로고
    • Segmentation of Polarimetric Synthetic Aperture Radar Data
    • E. Rignot and R. Chellappa, "Segmentation of Polarimetric Synthetic Aperture Radar Data," IEEE Trans. Image Processing, vol. 1, no. 3, pp. 281-300, 1992.
    • (1992) IEEE Trans. Image Processing , vol.1 , Issue.3 , pp. 281-300
    • Rignot, E.1    Chellappa, R.2
  • 40
    • 1242295887 scopus 로고    scopus 로고
    • SAR Sea Ice Recognition Using Texture Methods,
    • master's thesis, Dept. of System Design Eng, Univ. of Waterloo
    • B. Yue, "SAR Sea Ice Recognition Using Texture Methods," master's thesis, Dept. of System Design Eng., Univ. of Waterloo, 2001.
    • (2001)
    • Yue, B.1
  • 41
    • 0032687294 scopus 로고    scopus 로고
    • Estimation of Markov Random Field Prior Parameters Using Markov Chain Monte Carlo Maximum Likelihood
    • X. Descombes, R.D. Morris, J. Zerubia, and M. Berthod, "Estimation of Markov Random Field Prior Parameters Using Markov Chain Monte Carlo Maximum Likelihood," IEEE Trans. Image Processing, vol. 8, no. 7, pp. 954-963, 1999.
    • (1999) IEEE Trans. Image Processing , vol.8 , Issue.7 , pp. 954-963
    • Descombes, X.1    Morris, R.D.2    Zerubia, J.3    Berthod, M.4
  • 42
    • 0141879236 scopus 로고    scopus 로고
    • Model Selection and Minimum Description Length Principle
    • M. Hansen and B. Yu, "Model Selection and Minimum Description Length Principle," J. Am. Statistic Assoc., vol. 96, pp. 746-774, 2001.
    • (2001) J. Am. Statistic Assoc , vol.96 , pp. 746-774
    • Hansen, M.1    Yu, B.2
  • 44
    • 0016329473 scopus 로고
    • Decision Theory and Artificial Intelligence I: Semantics-Based Region Analyzer
    • J.A. Feldman and Y. Yakimovsky, "Decision Theory and Artificial Intelligence I: Semantics-Based Region Analyzer," Artificial Intelligence, vol. 5, no. 4, pp. 349-371, 1974.
    • (1974) Artificial Intelligence , vol.5 , Issue.4 , pp. 349-371
    • Feldman, J.A.1    Yakimovsky, Y.2
  • 46
    • 36349035278 scopus 로고    scopus 로고
    • SAR Sea-Ice Image Analysis Based on Iterative Region Growing Using Semantics
    • Q. Yu and D.A. Clausi, "SAR Sea-Ice Image Analysis Based on Iterative Region Growing Using Semantics," IEEE Trans. Geoscience and Remote Sensing, vol. 45, no. 12, 2007.
    • (2007) IEEE Trans. Geoscience and Remote Sensing , vol.45 , Issue.12
    • Yu, Q.1    Clausi, D.A.2
  • 47
    • 0035272740 scopus 로고    scopus 로고
    • Color Image Segmentation and Parameter Estimation in a Markovian Framework
    • Z. Kato, T.C. Pong, and J.C.M. Lee, "Color Image Segmentation and Parameter Estimation in a Markovian Framework," Pattern Recognition Letters, vol. 22, no. 3-4, pp. 309-321, 2001.
    • (2001) Pattern Recognition Letters , vol.22 , Issue.3-4 , pp. 309-321
    • Kato, Z.1    Pong, T.C.2    Lee, J.C.M.3
  • 48
  • 49
    • 0029359576 scopus 로고
    • A Finite Mixture Algorithm for Finding Proportions in SAR Images
    • R. Samadani, "A Finite Mixture Algorithm for Finding Proportions in SAR Images," IEEE Trans. Image Processing, vol. 4, no. 8, pp. 1182-1186, 1995.
    • (1995) IEEE Trans. Image Processing , vol.4 , Issue.8 , pp. 1182-1186
    • Samadani, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.