메뉴 건너뛰기




Volumn 11, Issue 8, 2011, Pages 5205-5214

SAR image segmentation based on artificial bee colony algorithm

Author keywords

ABC algorithm; Grey entropy; Image segmentation; SAR image

Indexed keywords

ARTIFICIAL BEE COLONIES; ARTIFICIAL FISH; CO-OCCURRENCE-MATRIX; FILTERED IMAGES; FITNESS FUNCTIONS; GRADIENT IMAGES; GRAY SCALE; GREY NUMBER; GREY THEORY; HIGH FREQUENCY HF; HONEY BEE; LOW FREQUENCY; OPTIMAL THRESHOLD; ORIGINAL IMAGES; SAR IMAGE; SAR IMAGE SEGMENTATION; SEARCH PROCEDURES; SEGMENTATION ACCURACY; SEGMENTATION METHODS; SPECKLE NOISE; SWARM INTELLIGENCE; SYNTHETIC APERTURE RADAR IMAGES; THRESHOLD ESTIMATION;

EID: 80053571767     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2011.05.039     Document Type: Article
Times cited : (175)

References (28)
  • 1
    • 0035294788 scopus 로고    scopus 로고
    • Segmentation of SAR images
    • DOI 10.1016/S0031-3203(01)00070-X, PII S003132030100070X
    • A. El Zaart, D. Ziou, S. Wang, and Q. Jiang Segmentation of SAR images Pattern Recognition 35 3 2002 713 724 (Pubitemid 34034606)
    • (2001) Pattern Recognition , vol.35 , Issue.3 , pp. 713-724
    • El Zaart, A.1    Ziou, D.2    Wang, S.3    Jiang, Q.4
  • 2
    • 33845410935 scopus 로고    scopus 로고
    • A survey of threshold methods for image segmentation
    • 102
    • S.Q. Han, and L. Wang A survey of threshold methods for image segmentation Systems Engineering and Electronics 24 6 2002 91 94 102
    • (2002) Systems Engineering and Electronics , vol.24 , Issue.6 , pp. 91-94
    • Han, S.Q.1    Wang, L.2
  • 4
    • 0000896186 scopus 로고
    • A comparative performance study of several global thresholding techniques for segmentation
    • S.U. Lee, S.Y. Chung, and R.H. Park A comparative performance study of several global thresholding techniques for segmentation Computer Vision Graphics Image Process 52 2 1990 171 190
    • (1990) Computer Vision Graphics Image Process , vol.52 , Issue.2 , pp. 171-190
    • Lee, S.U.1    Chung, S.Y.2    Park, R.H.3
  • 5
    • 0034427777 scopus 로고    scopus 로고
    • Nature-inspired computing technology and applications
    • P. Marrow Nature-inspired computing technology and applications BT Technology Journal 18 4 2000 13 23 (Pubitemid 32871711)
    • (2000) British Telecom technology journal , vol.18 , Issue.4 , pp. 13-23
    • Marrow, P.1
  • 6
    • 80053576235 scopus 로고    scopus 로고
    • Application of swarm intelligence in image processing
    • Y.Q. Wang, and W.Y. Liu Application of swarm intelligence in image processing Computer Applications 27 7 2007 1647 1650
    • (2007) Computer Applications , vol.27 , Issue.7 , pp. 1647-1650
    • Wang, Y.Q.1    Liu, W.Y.2
  • 7
    • 56349097213 scopus 로고    scopus 로고
    • Application of the genetic algorithm in image processing
    • Y. Tian, and W.Q. Yuan Application of the genetic algorithm in image processing Journal of Image and Graphics 12 3 2007 389 396
    • (2007) Journal of Image and Graphics , vol.12 , Issue.3 , pp. 389-396
    • Tian, Y.1    Yuan, W.Q.2
  • 8
    • 37849047299 scopus 로고    scopus 로고
    • A hybrid approach using Gaussian smoothing and genetic algorithm for multilevel thresholding
    • C.C. Lai, and D.C. Tseng A hybrid approach using Gaussian smoothing and genetic algorithm for multilevel thresholding International Journal of Hybrid Intelligent Systems 1 3 2004 143 152
    • (2004) International Journal of Hybrid Intelligent Systems , vol.1 , Issue.3 , pp. 143-152
    • Lai, C.C.1    Tseng, D.C.2
  • 9
    • 0042235430 scopus 로고    scopus 로고
    • A GA based approach for boundary detection of left ventricle with echocardio graphic image sequences
    • A. Mishraa, P.K. Dutta, and M.K. Ghoshc A GA based approach for boundary detection of left ventricle with echocardio graphic image sequences Image and Vision Computing 21 11 2003 967 976
    • (2003) Image and Vision Computing , vol.21 , Issue.11 , pp. 967-976
    • Mishraa, A.1    Dutta, P.K.2    Ghoshc, M.K.3
  • 10
    • 0142088890 scopus 로고    scopus 로고
    • Image segmentation by three-level thresholding based on maximum fuzzy entropy and genetic algorithm
    • W.B. Tao, J.W. Tian, and J.J. Liu Image segmentation by three-level thresholding based on maximum fuzzy entropy and genetic algorithm Pattern Recognition Letters 24 16 2003 3069 3078
    • (2003) Pattern Recognition Letters , vol.24 , Issue.16 , pp. 3069-3078
    • Tao, W.B.1    Tian, J.W.2    Liu, J.J.3
  • 11
    • 0032737679 scopus 로고    scopus 로고
    • A fast scheme for optimal thresholding using genetic algorithms
    • P.Y. Yin A fast scheme for optimal thresholding using genetic algorithms Signal Processing 72 2 1999 85 95
    • (1999) Signal Processing , vol.72 , Issue.2 , pp. 85-95
    • Yin, P.Y.1
  • 12
    • 0036622452 scopus 로고    scopus 로고
    • 2-D maximum entropy method of image segmentation based on genetic algorithm
    • G. Chen, and H.F. Zuo 2-D maximum entropy method of image segmentation based on genetic algorithm Journal of Computer-Aided Design &Computer Graphics 14 6 2002 530 534
    • (2002) Journal of Computer-Aided Design &computer Graphics , vol.14 , Issue.6 , pp. 530-534
    • Chen, G.1    Zuo, H.F.2
  • 13
    • 73349118745 scopus 로고    scopus 로고
    • Fast SAR image segmentation method based on the two-dimensional grey entropy model
    • M. Ma, Y.J. Lu, Y.N. Zhang, and X.L. He Fast SAR image segmentation method based on the two-dimensional grey entropy model Journal of Xidian University 36 6 2009 1114 1119
    • (2009) Journal of Xidian University , vol.36 , Issue.6 , pp. 1114-1119
    • Ma, M.1    Lu, Y.J.2    Zhang, Y.N.3    He, X.L.4
  • 16
    • 33845523370 scopus 로고    scopus 로고
    • Ant colony optimization with active contour models for image segmentation
    • X.N. Wang, Y.J. Feng, and Z.R. Feng Ant colony optimization with active contour models for image segmentation Control Theory and Applications 23 4 2006 515 522
    • (2006) Control Theory and Applications , vol.23 , Issue.4 , pp. 515-522
    • Wang, X.N.1    Feng, Y.J.2    Feng, Z.R.3
  • 18
    • 14644420283 scopus 로고    scopus 로고
    • Infrared image segmentation with 2-D maximum entropy method based on particle swarm optimization
    • F. Du, W.K. Shi, L.Z. Chen, Y. Deng, and Z.F. Zhu Infrared image segmentation with 2-D maximum entropy method based on particle swarm optimization Pattern Recognition Letters 26 5 2005 597 603
    • (2005) Pattern Recognition Letters , vol.26 , Issue.5 , pp. 597-603
    • Du, F.1    Shi, W.K.2    Chen, L.Z.3    Deng, Y.4    Zhu, Z.F.5
  • 19
    • 70350517818 scopus 로고    scopus 로고
    • The two-dimensional Otsu thresholding based on fish-swarm algorithm
    • Z. Pan, and Y.Q. Wu The two-dimensional Otsu thresholding based on fish-swarm algorithm Acta Optica Sinica 29 8 2009 2115 2121
    • (2009) Acta Optica Sinica , vol.29 , Issue.8 , pp. 2115-2121
    • Pan, Z.1    Wu, Y.Q.2
  • 20
    • 75149134664 scopus 로고    scopus 로고
    • A survey: Algorithms simulating bee swarm intelligence
    • D. Karaboga, and B. Akay A survey: algorithms simulating bee swarm intelligence Artificial Intelligence Review 31 2009 61 85
    • (2009) Artificial Intelligence Review , vol.31 , pp. 61-85
    • Karaboga, D.1    Akay, B.2
  • 21
    • 77649232076 scopus 로고    scopus 로고
    • Honey Bees Mating Optimization algorithm for financial classification problems
    • M. Marinaki, Y. Marinakis, and C. Zopounidis Honey Bees Mating Optimization algorithm for financial classification problems Applied Soft Computing 10 3 2010 806 812
    • (2010) Applied Soft Computing , vol.10 , Issue.3 , pp. 806-812
    • Marinaki, M.1    Marinakis, Y.2    Zopounidis, C.3
  • 22
    • 33747621841 scopus 로고    scopus 로고
    • Honey-bees mating optimization (HBMO) algorithm: A new heuristic approach for water resources optimization
    • DOI 10.1007/s11269-005-9001-3
    • O.B. Haddad, A. Afshar, and M.A. Marino Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization Water Resources Management 20 2006 661 680 (Pubitemid 44263967)
    • (2006) Water Resources Management , vol.20 , Issue.5 , pp. 661-680
    • Haddad, O.B.1    Afshar, A.2    Marino, M.A.3
  • 23
    • 34248577020 scopus 로고    scopus 로고
    • Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation
    • DOI 10.1016/j.jfranklin.2006.06.001, PII S0016003206000822
    • A. Afshar, O.B. Haddad, M.A. Marino, and B.J. Adams Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation Journal of the Franklin Institute 344 2007 452 462 (Pubitemid 46764340)
    • (2007) Journal of the Franklin Institute , vol.344 , Issue.5 , pp. 452-462
    • Afshar, A.1    Bozorg Haddad, O.2    Marino, M.A.3    Adams, B.J.4
  • 25
    • 35148821762 scopus 로고    scopus 로고
    • A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm
    • DOI 10.1007/s10898-007-9149-x
    • D. Karaboga, and B. Basturk A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm Journal of Global Optimization 39 3 2007 459 471 (Pubitemid 47551831)
    • (2007) Journal of Global Optimization , vol.39 , Issue.3 , pp. 459-471
    • Karaboga, D.1    Basturk, B.2
  • 26
    • 34548479029 scopus 로고    scopus 로고
    • On the performance of artificial bee colony (ABC) algorithm
    • DOI 10.1016/j.asoc.2007.05.007, PII S1568494607000531
    • D. Karaboga, and B. Basturk On the performance of artificial bee colony (ABC) algorithm Applied Soft Computing 8 1 2008 687 697 (Pubitemid 47374599)
    • (2008) Applied Soft Computing Journal , vol.8 , Issue.1 , pp. 687-697
    • Karaboga, D.1    Basturk, B.2
  • 28
    • 10644263328 scopus 로고
    • Gray level-gradient cooccurrence matrix texture analysis method
    • J.G. Hong Gray level-gradient cooccurrence matrix texture analysis method Acta Automatica Sinica 10 1 1984 22 25
    • (1984) Acta Automatica Sinica , vol.10 , Issue.1 , pp. 22-25
    • Hong, J.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.