A multi-population genetic algorithm for robust and fast ellipse detection

Pattern Analysis and Applications

Volumn 8, Issue 1-2, 2005, Pages 149-162

  Yao, Jie ^a   Kharma, Nawwaf ^a   Grogono, Peter ^a  

^a Civil and Environmental Engineering   (Canada)

Author keywords

Clustering; Ellipse detection; Genetic algorithms; Multi modal problems; Randomized hough transform; Shape detection; Sharing GA

Indexed keywords

EID: 27844540367     PISSN: 14337541     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10044-005-0252-7     Document Type: Article

References (31)

1. Ballard DH (1981) Generalizing the hough transform to detect arbitrary shapes. Pattern Recognit 13(2):111-122
2. Chakraborty S, Deb K (1998) Analytic curve detection from a noisy binary edge map using genetic algorithm. PPSN, pp 129-138
3. Goldberg DE, Richardson J (1987) Genetic algorithms with sharing for multimodal function optimization. In: Grefenstette JJ (ed) Proceeding of the 2nd international conference on genetic algorithms. Lawrence Erlbaum, Hillsdale, pp 41-49
4. Grimson WEL, Huttenlocher DP (1990) On the sensitivity of the Hough transform for object recognition. IEEE Trans Pattern Anal Mach Intel 12(3):255-274
5. Guil N, Zapata EL (1997) Lower order circle and ellipse Hough transform. Pattern Recognit 30(10):1729-1744
6. Hearn, Baker MP (1997) Computer graphics C, Version D. Prentice Hall, Eagleeood Cliff
7. Ho CTA, Chen LH (1995) A fast ellipse/circle detector using geometric symmetry. Pattern Recognit 28(1):117-124
8. Hough PVC (1959) Machine analysis of bubble chamber pictures. In: International conference on high energy accelerators and instrumentation, CERN
9. Lei Y, Wong KC (1999) Ellipse detection based on symmetry. Pattern Recognit Lett 20(1):41-47
10. Lutton E, Martinez P (1994) A genetic algorithm for the detection of 2D geometric primitives in images. In: Proceedings of the 12th international conference on pattern recognition, Jerusalem, Israel, 9-13 October 1994, 1:526-528
11. Mainzer T (2002) Genetic algorithm for traffic sign detection. Appl Electron
12. Mainzer T (2002) Genetic algorithm for shape detection, Technical report no. DCSE/TR-2002-06, University of West Bohemia
13. McLaughlin RA (1998) Randomized hough transform: improved ellipse detection with comparison. Pattern Recognit Lett 19(3-4):299-305
14. Procter S, Illingworth J. A comparison of the randomized hough transform and a genetic algorithm for ellipse detection. In: Gelsema E, Kanal L (eds) Pattern recognition in practice IV: multiple paradigms, comparative studies and hybrid systems. Elsevier Science Ltd., pp 449-460
15. Roth G, Levine MD (1994) Geometric primitive extraction using a genetic algorithm. IEEE Trans Pattern Anal and Mach Intel 16(9):901-905
16. Smith RE, Forrest S, Perelson AS (1992) Searching for diverse, cooperative populations with genetic algorithms, TCGA Report No. 92002, The University of Alabama, Department of Engineering Mechanics
17. Press WH et al (1992) Numerical recipes in C, The art of scientific computing, 2nd edn, Chapter 2. Cambridge University Press, pp 43-50
18. Xu L, Oja E, Kultanen P (1990) A new curve detection method: randomized hough transform (RHT). Pattern Recognit Lett 11(5):331-338
19. Kim E, Haseyama M, Kitajima H (2002) Fast and robust ellipse extration from complicated images, in: International conference on informatio technology and applications
20. Ke Q, Jiang T, Ma S (1997) A tabu search method for geometric primitive extraction. Pattern Recognit Lett 18(14):1443-1452
21. McLaughlin RA, Alder MD (1998) The hough transform versus the upwrite. IEEE Trans Pattern Anal Mach Intel 20(4):396-400
22. Zhang SC, Liu ZQ (2005) A robust, real-time ellipse detector. Pattern Recognit 38:273-287
23. Xie Y, Ji Q (2002) A new efficient ellipse detection method. ICPR, pp 957-960
24. Cheng Z, Liu Y (2004) Efficient technique for ellipse detection using restricted randomized hough transform, in: International conference on information technology: coding and computing
25. Kasemir K.U, Betzler K (2003) Detecting ellipses of limited eccentricity in images with high noise levels. Image Vision Comput 21:221-227
26. Yin PY (1999) A new circle/ellipse detector using genetic algorithms. Pattern Recognit Lett 20:731-740
27. Roth G, Levine MD (1993) Extracting geometric primitives. CVGIP: image understanding 58(1):1-22
28. Jong KAD (1975) An analysis of the behavior of a class of genetic adaptive systems. PhD Thesis. University of Michigan
29. Ursem RK (1999) Multinational evolutionary algorithms, in; Proceedings of the congress on evolutionary computation 3:1633-1640
30. Tsutsui S, Fujimoto Y (1993) Forking genetic algorithm with blocking and shrinking modes (FGA). In: Proceedings of the 5th international conference on genetic algorithms, pp 206-215
31. Coello C, Carlos A (2000) An updated survey of GA-based multiobjective optimization techniques. ACM Comput Surv 32(2):109-143