David Casasent

Carnegie Mellon University

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Demetri Psaltis

École Polytechnique Fédérale de Lausanne

Tien‐Hsin Chao

National Cheng Kung University

Ashit Talukder

Moody's Corporation (United States)

Frank M. Caimi

Orthopaedic Center of Vero Beach

Ernest L. Hall

Baker Hughes (United States)

Etienne Barnard

North-West University

Songyot Nakariyakul

Thammasat University

Rohit Patnaik

Decision Sciences International Corporation (United States)

B. V. K. Vijaya Kumar

M S Ramaiah University of Applied Sciences

Brian A. Telfer

MIT Lincoln Laboratory

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Photo-DKDP light valve in optical data processing

Applied Optics (1979)

David Casasent Thanh Luu

Various real-time optical data processing experimentst using the photo-DKDP spatial light modulator are described. These include the performance of image subtraction and contrast reversal directly on the light valve and their application to practical pattern recognition situations in which the input and reference objects differ. Examples of real-time optical correlation on coded waveforms for signal processing are presented, and the accuracy of the optically produced ambiguity function outputs are compared to the theoretically expected ones. Real-time optical image pattern recognition experiments are also presented, together with comparative data obtained with off-line correlations performed using film.

Optical correlator

Subtraction

Stray light

Data Processing

Spatial frequency

Optical transfer function

Spatial light modulator

Light intensity

10.1364/ao.18.003307

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Citations (7)

Optical Linear Algebra Processors

Elsevier eBooks (1987)

David Casasent B. V. K. Vijaya Kumar

Linear algebra

Algebraic equation

Numerical Linear Algebra

Linear equation

10.1016/b978-0-12-355760-5.50016-8

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Citations (2)

<title>Detection and classification in SAR using MINACE correlation filters</title>

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1995)

David Casasent Rajesh Shenoy

New shift-invariant distortion-invariant SAR filters for detection and classification are described. They employ new modified MINACE filters. Test results are provided for real SAR data with 360 degree aspect views of 2 different objects and for 100 real SAR clutter chips (natural and man-made) that passed the second stage of the Lincoln Laboratory's SAR processor. We obtained P_D equals 100% and P_FA <EQ 0.82%. The shift-invariance of the filters allow their use as adjuncts for all stages (detection, discrimination, recognition) of a SAR image processor.

10.1117/12.210861

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Citations (1)

Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling

David Casasent

Active vision

Machine Vision

Robot vision

Source

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Citations (17)

<title>Nonlinear features for improved pattern recognition</title>

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2001)

David Casasent Ashit Talukder

Nonlinear features that represent higher-order correlations in input data are considered for improved recognition. They optimize new performance measures that do not make Gaussian etc. data distribution assumptions and that are intended for improved discrimination. The new features are produced in closed-form and are thus preferable to iterative solutions. An efficient two-step feature extraction algorithm is presented for the high-dimensional (iconic) input data case of most interest. The feature generation can be realized as a new neural network with adaptive activation functions. Test results on pose-invariant face recognition are emphasized; results on standard feature inputs for a product inspection application are briefly noted as a low- dimensional input data case.

Feature (linguistics)

10.1117/12.432795

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Citations (1)

<title>Pose estimation and transformation of faces</title>

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1998)

Ashit Talukder David Casasent

A new technique is discussed to estimate the pose (orientation) of unknown human faces from 2D gray-scale images and then transform the unknown face to a reference pose using a nonlinear feature extraction procedure. This feature extraction scheme is known as the maximum representation and discrimination feature (MRDF) method. The MRDF is shown to provide good features for discrimination between classes that is useful for pose estimation, and for object representation that is useful for pose transformation of an unknown face. Our approach is computationally efficient and has numerous potential applications, including post-invariant face recognition.

Representation

Feature (linguistics)

10.1117/12.325803

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Citations (6)

Optical Data Processing

Topics in applied physics (1978)

David Casasent

10.1007/bfb0057980

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Citations (95)

Intelligent robots and computer vision XIII : algorithms and computer vision : 31 October-2 November 1994, Boston, Massachusetts