Abstract
This paper presents a synergistic methodology for automatically recording, monitoring and interrelating changes occurred in invivo bio-cells without any user’s assistance. The methodology presented here combines several techniques, such as projection functions, registration, segmentation with region synthesis, local-global graphs and stochastic Petri-nets. Each of these techniques produces complementary results and the synergistic combination of them generates a methodology that produces the bio-signatures of bio-cells in sequences of images. Illustrative results are also provided.
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References
M. Kutter and F. A. P. Petitcolas, “A fair benchmark for image watermarking systems”, Electronic Imaging’ 99. Security and Watermarking of Multimedia Contents, ISOE, Vol. 3657, San Jose, CA, Jan 1999.
J. A. Saghri, P. S. Cheatham, a. Habibi, “Image Quality Measure Based on Human Visual System Model”, Optical Engineering, Vol. 28, No. 7, July 1989
D. J. Fleet and D. J. Heeger, “Embedding Invisible Information in Color Images”, Proc. of the ICIP, pp. 532–535, Santa Barbara, California, Oct 1997
Mark D. Fairchild, Color Appearance Models, Addison Wesley Longman, Inc., 1998
N. Bourbakis, Emulating human visual perception for measuring differences in images using an SPN graph approach, IEEE T-SMC, 32,2, 191–201, 2002
A. Moghaddamzadeh and N. Bourbakis, “A Fuzzy Region Growing Approach For Segmentation of Color Images”, Pattern Recognition, Vol. 30, No. 6, pp. 867–881, 1997
N. Bourbakis, Detecting differences in sequences of images using PFF and LGG, IEEE Conf. TAI-2002, Nov. 2002, VA, pp. 355–362.
S. Makrogiannis and N. Bourbakis, Stochastic optimization scheme for automatic registration of aerial images, IEEE TAI-2004, FL, Nov. 15–17, 2004, pp. 328–336.
N. Bourbakis, J. Gattiker and G. Bebis Representing and interpreting human activity and events from video, Int. JAIT, vol. 12,1,2003.
N. Bourbakis, Emulating human visual perception for measuring differences in images using an SPN graph approach, IEEE T-SMC, 32,2, 191–201, 2002.
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© 2006 International Federation for Information Processing
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Bourbakis, N. (2006). Recording, Monitoring and Interrelating Changes of Invivo Bio-cells from Video (Biosignatures) . In: Maglogiannis, I., Karpouzis, K., Bramer, M. (eds) Artificial Intelligence Applications and Innovations. AIAI 2006. IFIP International Federation for Information Processing, vol 204. Springer, Boston, MA . https://doi.org/10.1007/0-387-34224-9_54
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DOI: https://doi.org/10.1007/0-387-34224-9_54
Publisher Name: Springer, Boston, MA
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