The regular polygon detector

Pattern Recognition

Volumn 43, Issue 3, 2010, Pages 592-602

  Barnes, Nick ^a,b   Loy, Gareth ^c   Shaw, David ^a,b  

^a CSIRO   (Australia)

^b AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^c ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

Author keywords

Regular polygon detection; Shape detection; Sign recognition

Indexed keywords

A-POSTERIORI PROBABILITIES; DRIVER ASSISTANCE; IMAGE EDGE; REGULAR POLYGON; SEARCH SPACES; SHAPE DETECTION; SIGN DETECTION; SIGN RECOGNITION; THREE DIMENSIONS;

AUTOMOBILE DRIVERS; DETECTORS; MAXIMUM LIKELIHOOD;

PROBABILITY DENSITY FUNCTION;

EID: 70449720555     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2009.09.008     Document Type: Article

References (31)

1. Ballard D.H. Generalizing the hough transform to detect arbitrary shapes. Pattern Recognition 13 2 (1981) 111-122
2. N. Barnes, G. Loy, Real-time regular polygonal sign detection, in: Proceedings of the 5th International Conference on Field and Service Robotics (FSR05), 2005.
3. N. Barnes, G. Loy, D. Shaw, A. Robles-Kelly, Regular polygon detection, in: International Conference on Computer Vision, 2005.
4. Barnes N., Zelinsky A., and Fletcher L. Real-time speed sign detection using the radial symmetry detector. IEEE Transactions on Intelligent Transportation Systems 9 2 (2008) 321-332
5. Castano R.L., and Hutchinson S. A probabilistic approach to perceptual grouping. Computer and Vision Image Understanding 64 3 (1996) 399-419
6. Cox I.J., Rehg J.M., and Hingorani S.L. A Bayesian multiple hypothesis approach to contour segmentation. International Journal of Computer Vision 11 (1993) 5-24
7. Crevier D. A probabilistic method for extracting chains of collinear segments. Image and Vision Computing 76 1 (1999) 36-53
8. Dickson W. Feature grouping in a hierarchical probabilistic network. Image and Vision Computing 9 1 (1991) 51-57
9. Gavrila D.M. A road sign recognition system based on dynamic visual model. Proceedings of the 14th International Conference on Pattern Recognition vol. 1 (1998) 16-20
10. C. Geyer, S. Sastry, R. Bajcsy, Euclid meets fourier: applying harmonic analysis to essential matrix estimation in omnidirectional cameras, in: OMNIVIS'04, 2004.
11. Guy G., and Medioni G. Inferring global perceptual contours from local features. International Journal of Computer Vision 20 1-2 (1996) 113-133
12. P.V.C. Hough, Method and means for recognizing complex patterns, (3,069,654), U.S. Patent, 3,069,654, 1962.
13. Hsu S.H., and Huang C.L. Road sign detection and recognition using matching pursuit method. Image and Vision Computing 19 (2001) 119-129
14. Huddleston J.N., and Ben-Arie J. Grouping edgels into structural entities using circular symmetry, the distributed hough transform and probabilistic non-accidentalness. CVGIP: Image Understanding 57 2 (1993) 227-242
15. Kiryati N., and Bruckstein A.M. Heteroscedastic Hough transform (HTHT): an efficient method for robust line fitting in the 'errors in the variables' problem. Computer Vision and Image Understanding 78 1 (2000) 69-83
16. Lowe D.G. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60 2 (2004) 91-110
17. G. Loy, N. Barnes, Fast shape-based road sign detection for a driver assistance system, in: Proceedings of the 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS2004, 2004.
18. Loy G., and Zelinsky A. Fast radial symmetry for detecting points of interest. IEEE Transactions on Pattern Analysis and Machine Intelligence 25 8 (2003) 959-973
19. Maldonado-Bascon S., Laufente-Arroyo S., Gil-Jimenez P., Gomez-Moreno H., and Lopez-Ferreras F. Road-sign detection and recognition based on support vector machines. IEEE Transactions on Intelligent Transportation Systems 8 2 (2007) 264-278
20. Minor L.G., and Sklansky J. Detection and segmentation of blobs in infrared images. IEEE Transactions on Systems, Man, and Cybernetics 11 3 (1981) 194-201
21. Parent P., and Zucker S.W. Trace inference, curvature consistency, and curve detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 11 8 (1989) 823-839
22. P. Perona, W.T. Freeman, Factorization approach to grouping, in: European Conference on Computer Vision 1998, 1998, pp. 655-670.
23. Piccioli G., Micheli E.D., Parodi P., and Campani M. Robust method for road sign detection and recognition. Image and Vision Computing 14 3 (1996) 209-223
24. Priese L., Klieber J., Lakmann R., Rehrmann V., and Schian R. New results on traffic sign recognition. Proceedings of the Intelligent Vehicles Symposium (1994), IEEE Press, Paris 249-254
25. Robles-Kelly A., and Hancock E.R. A probabilistic spectral framework for grouping and segmentation. Pattern Recognition 37 7 (2004) 1387-1405
26. Sarkar S., and Boyer K.L. Quantitative measures of change based on feature organisation: eigenvalues and eigenvectors. Computer Vision and Image Understanding 71 1 (1998) 110-136
27. A. Shashua, S. Ullman, Structural saliency: the detection of globally salient structures using a locally connected network, in: Proceedings of the International Conference on Computer Vision, 1988, pp. 321-327.
28. D. Shaw, N. Barnes, Regular polygon detection as an interest point operator for slam, in: Proceedings of the 2004 Australasian Conference on Robotics and Automation, 2004 〈www.araa.asn.au/acra/acra2004〉.
29. Stephens R.S. Probabilistic approach to the Hough transform. Image and Vision Computing 9 1 (1991) 66-71
30. Weiman C.F.R., and Chaikin G. Logarithmic spiral grids for image processing and display. Computer Graphics and Image Processing 11 (1979) 197-226
31. Z. Zhang, Clustering or Hough transform, Technical Report, INRIA, 1996.