Image analysis – Histogram processing – For segmenting an image
Reexamination Certificate
2006-09-05
2006-09-05
Mehta, Bhavesh M. (Department: 2624)
Image analysis
Histogram processing
For segmenting an image
C382S170000, C382S172000
Reexamination Certificate
active
07103219
ABSTRACT:
A method and apparatus for determining the best fit of a population mixture model to data. In the digital imaging area, the use of histogram data is employed. A plurality of sub-population functions are defined and then optimized to fit the data. An objective function is employed, which is based upon the parameters of the underlying functions. The number of underlying functions is added to the parameter mix, such that no a priori knowledge of the number of sub-populations is required. In an illustrative embodiment, a genetic algorithm is used to evolve the objective function to an optimal fit of the data. Once an optimal fit is found, through comparison with stopping criteria in a fitness function, the data is segmented according to threshold determined based of classification error in the data.
REFERENCES:
patent: 5136686 (1992-08-01), Koza
patent: 6004015 (1999-12-01), Watanabe et al.
Neves, Nguyen, and Torres. “A Study of a Non-Linear Optimization Problem Using a Distributed Geenetic Algorithm”. Aug. 1996, Proceedings of the 1996 International Conference on Parallel Processing (ICPP '96)-vol. 2. pp. 29-36.
Martinez and Vitrià . “Learning Mixture Models Using a Genetic Version of the EM Algorithm”. Jul. 2000. Pattern Recognition Letters.vol. 21 , Issue 9 (Jul. 2000). pp. 759-769.
David Levine. “Statistics for Managers Using Microsoft Excel”—Powerpoint Presentation (Chapter 14: Multiple Regression Models). 1999 © Prentice Hall.
Press, Teukolsky, Vetterling and Flannery. “Numerical Recipes in C: The Art of Scientific Computing”. 1992 © Cambridge Univesity Press, 2nd Ed. pp. 656-657, 671-681.
M. Mitchell and S. Forrest, “Genetic Algorithms and Artificial Life”, Artificial Life, vol. 1, No. 3 (1994), pp. 267-289.
“Digital Image Processing” by Rafael C. Gonzales and Paul Wintz. Addison-Wesley Publishing Company, 1977, pp. 325-331.
“Global Optimization: Techniques and Applications” by Nathan D. Cahill. Rochester Institute of Technology Master's Thesis, May 1, 2000.
“Optimal Thresholding—A New Approach” by Wesley Snyder, Griff Bilbro, Ambalavaner Logenthiran and Sarah Rajala. Pattern Recognition Letters 11, 1990, pp. 803-810.
“Optimal histogram partitioning using a simulated annealing technique” by R. Brunelli. Pattern Recognition Letters, 13, 1992, pp. 581-586.
Eastman Kodak Company
Mehta Bhavesh M.
Tucker Wes
Woods David M.
LandOfFree
Population mixture modeling with an indeterminate number of... does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Population mixture modeling with an indeterminate number of..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Population mixture modeling with an indeterminate number of... will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3557338