Imaging and filters

Image processing has always been one of the my favourite and talked about subjects and un doubtly it is one of the most interesting bits of computer science that exist. For some it is a challenge to talk about, a few would term it as virtually impossible and a few would be developing applications from secure government projects to a simplistic robots. Image processing by far remains one of the most sophisticated technologies in the world today. The use of it can be seen in laboratories, industrial applications and also a few personal computing applications. Either we are using Document processing or scanning images; watching an assembly line guided by robots or using satellites is all that relates to image processing. Today image processing is part of our lives and for some a success story. Image processing is one field that is always taking its mark towards new ideas and innovations. My interest grows more every time I read something about Image processing and I write about it today. I had done a small project back in school with some hefty amounts of research, Ironically my career did not start off in a research lab just as I would have liked it to be but thats the “bit” we all try to understand *Try*, everyday. ­čÖé At that time my ultimate aim had been to choose an application that brings knowledge not only to me but also to my fellow colleagues, students of Asia Pacific Institute of Information Technology, friends and to give me a solid position in order to research further and probably in a laboratory fulfilling realities of science fiction.

Attached is a PDF [Imaging and Filters] of the extract. This piece of murky english that stays in my backup CD drives should be atleast out here in the virtual space. Maybe some one might benefit from my very little understanding of the matter.

Following are some really nice├é┬áreosurces to start your day with Image procesing├é┬á ­čśë

Rerources:

1. [HIPR2] 2002 http://www.dai.ed.ac.uk/HIPR2/hipr_top.htm
2. [Andy Salter] MSc Computing Science degree at Imperial College, Spline Curves
and Surfaces http://www.doc.ic.ac.uk/%7Edfg/AndysSplineTutorial/index.html.
3. [NEC] site ceer, http://citeseer.nj.nec.com
4. [Dr. Douglas A Lyon] 1999, Image Processing in java
5. [Dr. Douglas A Lyon] 1999, Morphological Filtering.
6. [Dr. Douglas A Lyon] 1999, Transformation and chromaticity.
7. R.-L. Hsu, M. Abdel-Mottaleb, and A. K. Jain, “Face detection in color images,”
IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 696-
706, May 2002. [PDF, TPAMI Journal paper]
<http://www.cse.msu.edu/~hsureinl/facloc/tpami113783_.pdf> [Hsu et Al.]
8. [JAI] 1997 Sun Microsystems. http://www.java.sun.com
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10. Object Detection Using the Statistics of Parts
H. Schneiderman and T. Kanade
International Journal of Computer Vision, 2002. [Abstract]
11. A histogram-based method for detection of faces and cars
H. Schneiderman and T. Kanade
Proceedings of the 2000 International Conference on Image Processing (ICIP ’00),
Vol. 3, September, 2000, pp. 504 – 507. [Abstract]
12. A Statistical Model for 3D Object Detection Applied to Faces and Cars
H. Schneiderman and T. Kanade
IEEE Conference on Computer Vision and Pattern Recognition, IEEE, June,
2000. [Abstract]
Bsc (Hons) Final Year Computing Appendix
Asia Pacific Institute of Information Technology 129
13. A Statistical Approach to 3D Object Detection Applied to Faces and Cars
H. Schneiderman
doctoral dissertation, tech. report 00-06, Robotics Institute, Carnegie Mellon
University, May, 2000. [Abstract]
14. Probabilistic Modeling of Local Appearance and Spatial Relationships for Object
Recognition
H. Schneiderman and T. Kanade
Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition (CVPR ’98), July, 1998, pp. 45-51. [Abstract]
15. Object Recognition by Computer: The Role of Geometric Constraints. Cambridge,
MA: MIT Press.Grimson, W. E. L. (1990).
16. Comparing images using the Hausdorff distance. IEEE Transactions on Pattern
Analysis and Machine Intelligence 15(9):850-863. Huttenlocher, D. P., G. A.
Klanderman, and W. J. Rucklidge. (1993).
17. On recognizing and positioning curved 3-D objects from image contours. IEEE
Transactions on Pattern Analysis and Machine Intelligence 12:1127-1137.
Kriegman, D. J., and J. Ponce. (1990).
18. [Gregory A Baxus] 1994, Shape Measurements, Digital Image Processing
19. [Gregory A Baxus] 1994, Image Operation Studies
20. [Donald Hearn] and [M Pauline Baker] 1994, Computer Graphics