
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
G. Roth, M.D. Levine, "Geometric Primitive Extraction Using a Genetic Algorithm," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 9, pp. 901905, September, 1994.  
BibTex  x  
@article{ 10.1109/34.310686, author = {G. Roth and M.D. Levine}, title = {Geometric Primitive Extraction Using a Genetic Algorithm}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {16}, number = {9}, issn = {01628828}, year = {1994}, pages = {901905}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.310686}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Geometric Primitive Extraction Using a Genetic Algorithm IS  9 SN  01628828 SP901 EP905 EPD  901905 A1  G. Roth, A1  M.D. Levine, PY  1994 KW  feature extraction; computer vision; genetic algorithms; optimisation; geometry; geometric primitive extraction; genetic algorithm; geometric sensor data; modelbased vision; minimal subset; random search; Hough transform VL  16 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
Extracting geometric primitives from geometric sensor data is an important problem in modelbased vision. A minimal subset is the smallest number of points necessary to define a unique instance of a geometric primitive. A genetic algorithm based on a minimal subset representation is used to perform primitive extraction. It is shown that the genetic approach is an improvement over random search and is capable of extracting more complex primitives than the Hough transform.
[1] M. Rioux, "Laser rangefinders based on synchronized scanning,"Applied Optics, vol. 23, pp. 38373844, 1985.
[2] J. Illingworth and J. Kittler, "A survey of the Hough transform,"Comput. Vision Graphics Image Processing, vol. 44, pp. 87116, 1988.
[3] D. Y. Kim, J. J. Kim, P. Meer, D. Mintz, and A. Rosenfeld, "Robust computer vision: A least median of squares based approach," inProc. DARPA Image Understanding Workshop, 1989.
[4] J. M. Jolion, P. Meer, and S. Bataouche, "Robust clustering with applications in computer vision,"IEEE Trans. Pattern Anal. Machine Intell., vol. 13, pp. 791802, 1991.
[5] A. Califano and R. Bolle, "The multiple window parameter transformation,"IEEE Trans. Pattern Anal. Machine Intell., vol. 14, pp. 11571170, 1992.
[6] D. J. Kriegman and J. Ponce, "On recognizing and positioning curved 3d objects from image contours,"IEEE Trans. Pattern Anal. Machine Intell., vol. 12, pp. 11271137, 1990.
[7] A. Hill and C. J. Taylor, "Modelbased image interpretation using genetic algorithms,"Image and Vision Computing, vol. 10, pp. 295300, 1992.
[8] G. Roth and M. D. Levine, "Extracting geometric primitives,"Comput. Vision, Graphics Image Processing: Image Understanding, vol. 58, pp. 122, 1993.
[9] J. H. Holland,Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press, 1975.
[10] D. E. Goldberg,Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: AddisonWesley, 1989.
[11] G. Roth and M. D. Levine, "A genetic algorithm for primitive extraction," inProc. Fourth Int. Conf. Genetic Algorithms, San Diego, CA, 1991, pp. 487494.
[12] T. W. Sederberg and D. C. Anderson, "Implicit representation of parametric curves and surfaces,"Comput. Vision, Graphics Image Processing, vol. 28, pp. 7284, 1984.
[13] R. C. Bolles and M. A. Fischler, "A ransacbased approach to model fitting and its application to finding cylinders in range data," inSeventh Int. Joint Conf. Artificial Intell., Vancouver, British Colombia, Canada, 1981, pp. 637643.
[14] G. Roth and M. D. Levine, "Segmentation of geometric signals using robust fitting," inProc. 10th Int. Conf. on Pattern Recognit., vol. 1, pp. 826831, 1990.
[15] P. Kultanen, L. Xu, and E. Oja, "Randomized Hough transform (RHT)," inProc. 10th Int. Conf. Patt. Recogn., June 1990, pp. 631635.
[16] W. M. Spears and K. A. DeJong, "On the virtues of parameterized uniform crossover," inProc. Third Int. Conf. Genetic AlgorithmsM. Kaufman, Ed., San Diego, CA, 1991, pp. 230236.
[17] G. Syswerda, "A study of reproduction in generational and steadystate genetic algorithms," inFoundations of Genetic Algorithms, G. Rawlins, Ed. San Mateo, CA: Morgan Kaufman, 1991, pp. 94101.
[18] G. Roth and M. D. Levine, "Geometric primitive extraction using a genetic algorithm," Tech. Rep. McRCIMTRCIM 9214, Comput. Vision and Robotics Lab., McGill Res. Ctr. for Intelligent Machines, McGill Univ., Montréal, Canada, Oct. 1992.
[19] B. Bhanu, S. Lee, and J. Ming, "Selfoptimizing image segmentation system using a genetic algorithm," inProc. Fourth Int. Conf. Genetic Algorithms, San Diego, CA, 1991, pp. 362369.
[20] D. B. Fogel,System identification through simulation evolution: a machine learning approach to modelling. Needham Heights, MA: Ginn Press, 1991.
[21] J. R. Kender and R. Kjeldsen, "On seeing spaghetti," inTwelfth Int. Joint Conf. Artificial Intell., Sydney, Australia, 1991, pp. 12711277.
[22] A. Rosenfeld, J. Ornelas, and Y. Hung, "Hough Transform Algorithms for MeshConnected SIMD Parallel Processors,"Computer Vision, Graphics and Image Processing, Vol. 41, No. 3, Mar. 1988, pp. 293305.