A Gaussian-mixture based approach to spatial image background modeling and compensation

European Signal Processing Conference

Volumn , Issue , 2007, Pages 1457-1461

  Saranli, Afsar ^a  

^a MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

BACKGROUND MODELING; BACKGROUND SIGNALS; BACKGROUND VARIATION; BIVARIATE; COMPACT REPRESENTATION; DEFECT DETECTION; GAUSSIAN FUNCTIONS; GAUSSIAN KERNELS; HIGH FREQUENCY; IMAGE PLANE; NON-UNIFORM ILLUMINATION; OPTICAL INSPECTION; PATTERNED MEDIAS; SPATIAL IMAGES; SUBPIXEL RESOLUTION; SURFACE IMAGE; TFT LCD PANELS; TWO-DIMENSIONAL ARRAYS;

OPTICAL TESTING; SIGNAL PROCESSING; THIN FILM TRANSISTORS;

INSPECTION;

EID: 84863742748     PISSN: 22195491     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. R. Chin, "Automated visual inspection: a survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 4, no. 6, pp. 557-573, 1982.
2. E. N. Malamas et al., "A survey on industrial vision systems, applications and tools," Image and Vision Computing, vol. 21, pp. 171-188, February 2003.
3. J. H. Kim et al., "A high speed high resolution system for the inspection of tft lcd," in Proceedings IEEE Int. Symp. Industrial Electronics, vol. 1, pp. 12-16, 2001.
4. C. Cho and other, "Development of real-time vision-based fabric inspection system," IEEE Transactions on Industrial Electronics, vol. 52, pp. 1073-1079, August 2005.
5. S. Bhandarkar and X. Luo, "Fast and robust background updating for real-time traffic surveillance and monitoring," in Proceedings of IEEE CS Conference on Computer Vision and Pattern Recognition, pp. 55-61, IEEE Computer Society, June 2005.
6. M. Cristani et al., "Integrated region- and pixel-based approach to background modelling," in Proceedings of Workshop on Motion and Video Computing, pp. 3-8, December 2002.
7. Z. Liu, K. Huang, T. Tan, and L. Wang, "Cast shadow removal with gmm for surface reflectance component," in Proceedings of the 18th International Conference on Pattern Recognition (ICPR'06), vol. 1, pp. 727-730, August 2006.
8. M. Harville, G. Gordon, and J. Woodfill, "Foreground segmentation using adaptive mixture models in color and depth," in Proceedings of IEEE Workshop on Detection and Recognition of Events in Video, pp. 3-11, IEEE, July 2001.
9. N. Friedman and S. Russel, "Image segmentation in video sequences: A probabilistic approach," in Proceedings of Thirteenth Annual Conference on Uncertainty in Artificial Intelligence, pp. 175-181, Morgan Kauffman Publishers Inc., 1997.
10. C. Stauffer and W. Grimson, "Adaptive background models for real-time tracking," in Proceedings of IEEE CS Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 246-252, IEEE Computer Society, 1999.
11. U. Garain et al., "On foreground-background separation in low quality color document images," in Proceedings of Eight International Conference on Document Analysis and Recognition, pp. 585-589, IEEE Computer Society, 2005.
12. S.-C. Hsia et al., "A cost-effective line-based light-balancing technique using adaptive processing," IEEE Transactions on Image Processing, vol. 15, no. 9, pp. 2719-2729, 2006.
13. D. G. Luenberger, Introduction to Linear and Nonlinear Programming. Addison-Wesley Pub. Co., 1973.