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A goal of the theoretical research at the Irvine Computer Vision Laboratory is to develop models and algorithms that are sufficiently robust and efficient to be employed for the solution of real problems in specific application areas. Achieving this goal is facilitated by attention to the development of efficient algorithms and careful experimentation with large sets of images. The first three references below describe real-time systems used for industrial inspection [1], target detection in infrared images [2], and fire detection [3]. Reference [4] uses a hierarchical segmentation algorithm for robust motion tracking. In [5] we introduce a method for selecting optimal color illumination for the inspection of plants. Reference [6] combines color constancy algorithms for illumination invariant recognition in satellite images. We are currently working on the classification and quantification of cells in brain images for diagnosis of Alzheimer's disease and other conditions.

[1] G. Healey and B. Dom

``Pattern Classification Algorithms for Real-Time Image Segmentation,'' Proceedings of the International Conference on Pattern Recognition, Atlantic City, June 1990. abstract

[2] S. Sridhar and G. Healey

``Point Target Detection in Spatially Varying Clutter,'' Proceedings of IEEE Workshop on Applications of Machine Vision, 1992. abstract

[3] G. Healey, D. Slater, T. Lin, B. Drda, D. Goedeke

``A System for Real-Time Fire Detection,'' Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 1993. abstract

[4] G. Healey

``A Hierarchical Segmentation-based Approach to Motion Analysis,'' Image and Vision Computing, 11(9):570-576, November 1993. abstract

[5] M. Vriesenga, G. Healey, J. Sklansky, K. Peleg

``Colored Illumination for Enhancing Discriminability in Machine Vision,'' Journal of Visual Communication and Image Representation, 6(3):244-255, September 1995. abstract

[6] G. Healey and A. Jain

``Retrieving Multispectral Satellite Images using Physics-based Invariant Representations,'' IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(8):842-848, August 1996. abstract

[7] D. Slater, G. Healey, P. Sheu, C. W. Cotman, J. Su, A. Wasserman and R. Shankle

``Application of Color Machine Vision Methodologies to the Quantification of Cell Populations in 3-D Brain Tissue Samples,'' Journal of Imaging Science and Technology, 42(3):234-240, May/June 1998. abstract

[8] S. Najand, D. Blough and G. Healey

``Forward and Inverse Model for the Intensity Dependent Spread Filter,'' Journal of the Optical Society of America A, 13(7):1305-1314, July 1996. abstract

[9] S. Najand, D. Blough and G. Healey

``Signal-to-Noise Ratio of the Intensity-Dependent Spread Filter and its Reconstruction,'' Journal of the Optical Society of America A, 15(5):1068-1076, May 1998. abstract

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Last modified: 28 July 1998