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Application of the projection-onto-constraint-sets algorithm for optical pattern recognition.

J Rosen, J Shamir

    Optics Letters
    |September 24, 2009
    PubMed
    Summary
    This summary is machine-generated.

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    Projection-onto-constraint sets offer an efficient method for creating synthetic discriminant functions in pattern recognition. This algorithm is implemented using a digital procedure with a simulated joint-transform correlator.

    Area of Science:

    • Computer Science
    • Signal Processing
    • Pattern Recognition

    Background:

    • Synthetic discriminant functions (SDFs) are crucial for pattern recognition systems.
    • Efficient algorithms are needed for constructing complex SDFs.

    Purpose of the Study:

    • To present an efficient algorithm for constructing synthetic discriminant functions.
    • To demonstrate the implementation of this algorithm using a simulated joint-transform correlator.

    Main Methods:

    • The study employs the projection-onto-constraint sets algorithm.
    • A digital procedure based on a simulated joint-transform correlator is utilized for implementation.

    Main Results:

    • The projection-onto-constraint sets algorithm proves to be an efficient method for SDF construction.

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    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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  • The digital implementation successfully integrates the algorithm with a simulated joint-transform correlator.

    • Conclusions:

    • The projection-onto-constraint sets algorithm is a viable and efficient approach for pattern recognition.
    • Simulated joint-transform correlators provide a practical platform for implementing such algorithms.