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Original Articles

Efficient grey-level image segmentation using an optimised MUSIG (OptiMUSIG) activation function

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Pages 1-39 | Received 28 Mar 2009, Accepted 06 Dec 2009, Published online: 22 Feb 2010

References

  • Gonzalez , R.C. and Woods , R.E. 2002 . Digital Image Processing , Upper Saddle River, NJ : Prentice-Hall .
  • Jain , A. , Murthy , M. and Flynn , P. 1999 . Data clustering: A review . ACM Comput. Surveys , 31 : 265 – 322 .
  • Felzenszwalb , P.F. and Huttenlocher , D.P. 2004 . Efficient graph-based image segmentation . Int. J. Comput. Vision , 59 ( 2 ) : 167 – 181 .
  • Liu , X. and Wang , D. 2006 . Image and texture segmentation using local spectral histograms . IEEE Trans. Image Process. , 15 ( 10 ) : 3066 – 3077 .
  • Yang , W. , Guo , L. , Zhao , T. and Xiao , G. 2007 . Improving watersheds image segmentation method with graph theory . 2nd IEEE Conference on Industrial Electronics and Applications , : 2550 – 2553 .
  • Shi , J. and Malik , J. 2000 . Normalized cuts and image segmentation . IEEE Trans. Pattern Anal. Mach. Intell. , 22 ( 8 ) : 888 – 905 .
  • Malik , J. , Belongie , S. , Leung , T. and Shi , J. 2001 . Contour and texture analysis for image segmentation . Int. J. Comput. Vision , 43 ( 1 ) : 7 – 27 .
  • Bezdek , J.C. 1981 . Pattern Recognition with Fuzzy Objective Function Algorithms , New York, NY : Plenum Press .
  • Ahmed , M.N. , Yamany , S.M. , Mohamed , N. , Farag , A.A. and Moriarty , T. 2002 . A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data . IEEE Trans. Med. Imaging , 21 : 193 – 199 .
  • Noordam , J.C. , van den Broek , W.H.A.M. and Buydens , L.M.C. 2000 . Geometrically guided fuzzy C-means clustering for multivariate image segmentation . Proc. Int. Conf. Pattern Recogn. , 1 : 462 – 465 .
  • Egmont-Petersen , M. and de Ridder , D. 2002 . Image processing using neural networks – a review . Pattern Recogn. , 35 ( 10 ) : 2279 – 2301 .
  • Choi , S.H. and Rockett , P. 2002 . The training of neural classifiers with condensed datasets . IEEE Trans. Syst. Man Cybern. Part B , 32 ( 2 ) : 202 – 206 .
  • Kohonen , T. 1989 . Self-Organization and Associative Memory , Berlin, Germany : Springer-Verlag .
  • Jiang , Y. and Zhou , Z. 2004 . SOM ensemble-based image segmentation . Neural Proc. Lett. , 20 ( 3 ) : 171 – 178 .
  • Freeman , R. , Yin , H. and Allinson , N.M. 2002 . Self-organising maps for tree view based hierarchical document clustering . IEEE Int. Joint Conf. Neural Netw. (IJCNN'02) , 2 : 1906 – 1911 .
  • Chang , P.L. and Teng , W.G. 2007 . Exploiting the self-organizing map for medical image segmentation . Twentieth IEEE International Symposium on Computer-Based Medical Systems , : 281 – 288 . 20-22 June
  • Reddick , W.E. , Glass , J.O. , Cook , E.N. , Elkin , T.D. and Deaton , R.J. 1997 . Automated segmentation and classification of multispectral magnetic resonance images of brain using artificial neural networks . IEEE Trans. Med. Imaging , 16 ( 6 ) : 911 – 918 .
  • Ghosh , A. , Pal , N.R. and Pal , S.K. 1993 . Self-organization for object extraction using a multilayer neural network and fuzziness measures . IEEE Trans. Fuzzy Syst. , 1 ( 1 ) : 54 – 68 .
  • Ghosh , A. and Sen , A. 2002 . Soft Computing Approach to Pattern Recognition and Image Processing , Singapore : World Scientific .
  • Bhattacharyya , S. , Dutta , P. and Maulik , U. 2008 . Self organizing neural network (SONN) based gray scale object extractor with a multilevel sigmoidal (MUSIG) activation function . Foundations Comput. Dec. Sci. , 33 ( 2 ) : 131 – 165 .
  • Goldberg , D.E. 1989 . Genetic Algorithm in Search Optimization and Machine Learning , New York, NY : Addison-Wesley .
  • Paulinas , M. and Uinskas , A. 2007 . A survey of genetic algorithms applications for image enhancement and segmentation . Inform. Technol. Control , 36 ( 3 ) : 278 – 284 .
  • Vito , D.G. and Giosue , L.B. 2005 . Image segmentation based on genetic algorithms combination . Int. Conf. Image Anal. Proc. , 3617 : 352 – 359 .
  • Pal , S.K. , Bandyopadhyay , S. and Murthy , C.A. 1998 . Genetic algorithms for generation of class boundaries . IEEE Trans. Syst., Man Cybern.-Part B: Cybern. , 28 ( 6 ) : 816 – 827 .
  • Tao , W.B. , Tian , J.W. and Liu , J. 2003 . Image segmentation by three-level thresholding based on maximum fuzzy entropy and genetic algorithm . Pattern Recogn. Lett. , 24 ( 16 ) : 3069 – 3078 .
  • Pignalberi , S. , Cucchiara , R. , Cinque , L. and Levialdi , S. 2003 . Tuning range image segmentation by genetic algorithm . EURASIP J. Appl. Signal Proc. , 2003 ( 8 ) : 780 – 790 .
  • Bandyopadhyay , S. , Murthy , C.A. and Pal , S.K. 1995 . Pattern classification with genetic algorithms . Pattern Recogn. Lett. , 16 ( 5 ) : 801 – 808 .
  • Bhanu , B. , Lee , S. and Ming , J. 1995 . Adaptive image segmentation using a genetic algorithm . IEEE Trans. Syst., Man, Cybern. , 25 ( 12 ) : 1543 – 1567 .
  • Murthy , C.A. and Chowdhury , N. 1996 . In search of optimal clusters using genetic algorithm . Pattern Recogn. Lett. , 17 : 825 – 832 .
  • Liu , J. and Yang , Y.H. 1994 . Multi-resolution color image segmentation . IEEE Trans. Pattern Anal. Mach. Intell. , 16 ( 7 ) : 689 – 700 .
  • Borsotti , M. , Campadelli , P. and Schettini , R. 1998 . Quantitative evaluation of color image segmentation results . Pattern Recogn. Lett. , 19 : 741 – 747 .
  • Zadeh , L.A. 1965 . Fuzzy sets . Inform. Control , 8 ( 1 ) : 338 – 353 .
  • Ross , T.J. and Ross , T. 1995 . Fuzzy Logic with Engineering Applications , New York, NY : McGraw-Hill, College Div. .
  • Graham , R. , McCabe , H. and Sheridan , S. 2003 . Pathfinding in computer games . ITB Journal , 8
  • Aranha , C. 2007 . Portfolio management by genetic algorithms with error modeling . Inform. Sci. , : 459 – 465 .
  • Zhang , H. , Fritts , J.E. and Goldman , S. 2004 . An entropy-based objective evaluation method for image segmentation , in Proceedings of SPIE Storage and Retrieval Methods and Applications for Multimedia
  • Zhang , Y. 1996 . A survey on evaluation methods for image segmentation . Pattern Recogn. , 29 ( 8 ) : 1335 – 1346 .

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