A new evolutionary algorithm for image segmentation

Lecture Notes in Computer Science

Volumn 3449, Issue , 2005, Pages 264-273

  Bocchi, Leonardo ^a   Ballerini, Lucia ^c   Hässier, Signe ^b  

^a UNIVERSITY OF FLORENCE   (Italy)

^b UPPSALA UNIVERSITY HOSPITAL   (Sweden)

^c NONE

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE ANALYSIS; IMAGE SEGMENTATION; MEDICAL IMAGING; SPURIOUS SIGNAL NOISE;

BIDIMENSIONAL WORLD; COLONIZATION; NOISE IMAGES; SEGMENTATION ALGORITHMS;

EVOLUTIONARY ALGORITHMS;

EID: 24644456053     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-32003-6_27     Document Type: Conference Paper

References (19)

1. Pal, N.R., Pal, S.K.: A review on image segmentation techniques. Pattern Recognition 26 (1993) 1277-1294
2. Jain, A.K.: Cluster analysis. In Young, T.Y., Fu, K.S., eds.: Handbook of Pattern Recognition and Image Processing. Academic Press (1986) 33-57
3. Cannon, R.L., Dave, J.V., Bezdek, J.C.: Efficient implementation of the fuzzy cmeans clustering algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-8 (1986) 248-255
4. Chi, Z., Yan, H., Pham, T.: Fuzzy algorithms: with application to image processing and pattern recognition. World Scientific, Singapore (1996)
5. Goldberg, D.E.: Genetic Algorithms in Seaxch, Optimization, and Machine Learning. Addison-Wesley, Reading, MA (1989)
6. Bezdek, J.C., Hathaway, R.J.: Optimization of fuzzy clustering criteria using genetic algorithms. In: Proc. 1st IEEE Conf. Evolutionary Computation. (1994) 589-549
7. Hall, L.O., Ozyurt, I.B., Bezdek, J.C.: Clustering with a genetically optimized approach. IEEE Transactions on Evolutionary Computation 3 (1999) 103-112
8. Ballerini, L., Bocchi, L., Johansson, C.B.: Image segmentation by a genetic fuzzy c-means algorithm using color and spatial information. In: Application of Evolutionary Computation. Number 3005 in Lectures Notes in Computer Science, Coimbra, Portugal (2004) 260-269
9. Bhanu, B., Lee, S., Ming, J.: Adaptive image segmentation using a genetic algorithm. IEEE Transactions on Systems, Man and Cybernetics 25 (1995) 1543-1567
10. Bhandarkar, S.M., Zhang, H.: Image segmentation using evolutionary computation. IEEE Transactions on Evolutionary Computation 3 (1999) 1-21
11. Andrey, P.: Selectionist relaxation: Genetic algorithms applied to image segmentation. Image and Vision Computing 17 (1999) 175-187
12. Liu, J., Tang, Y.Y.: Adaptive image segmentation with distributed behavior-based agents. IEEE Transactions on Pattern Analysis and Machine Intelligence 21 (1999) 544-551
13. Veenman, C.J., Reinders, M.J.T., Backer, E.: A cellular coevolutionary algorithm for image segmentation. IEEE Transactions on Image Processing 12 (2003) 304-313
14. Ramos, V., Almeida, F.: Artificial ant colonies in digital image habitats - a mass behaviour effect study on pattern recognition. In: Proc. of ANTS'2000 - 2nd Int. Workshop on Ant Algorithms (From Ant Colonies to Artificial Ants), Brussels, Belgium (2000) 113-116
15. Gardner, M.: The fantastic combinations of John Conway's new solitaire game "life". Scientifican American 223 (1970) 120-123
16. Lim, Y.W., Lee, S.U.: On the color image segmentation algorithm based on the thresholding and the fuzzy c-means techniques. Pattern Recognition 23 (1990) 1935-952
17. Xie, X.L., Beni, G.: A validity measure for fuzzy clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 13 (1991) 841-847
18. Hathaway, R.J., Bezdek, J.C.: Optimization of clustering criteria by reformulation. IEEE Transactions on Fuzzy Systems 3 (1995) 241-254
19. Stevens, A., Lowe, J.: Human Histology. C.V. Mosby, 2nd edition (1997)