Synthetic discriminant function fringe-adjusted joint transform correlator

Ruikang K. Wang; Christopher R. Chatwin; Lin Shang

doi:10.1117/12.210732

1 October 1995 Synthetic discriminant function fringe-adjusted joint transform correlator

Ruikang K. Wang, Christopher R. Chatwin, Lin Shang

Author Affiliations +

Optical Engineering, Vol. 34, Issue 10, (October 1995). https://doi.org/10.1117/12.210732

Abstract

A synthetic discriminant function (SDF) fringe-adjusted joint transform correlator is proposed that is able to provide a high degree of image distortion invariance and classify different objects in the input scene. The SDF reference function, which is displayed alongside the input scene, is a linear combination of the training image set. An iterative algorithm is presented and utilized to obtain the linear combination coefficients from the nonlinear equations of the fringe-adjusted joint transform correlation (JTC) system. When compared with the SDF-based classical JTC and binary JTC, the SDF fringe-adjusted JTC delivers a better capability to give localized equal correlation peak heights for the same class of objects. Furthermore, when the input scene contains the different objects from the different classes of images, the SDF fringe-adjusted JTC is shown to efficiently classify the different target objects and reject the nontarget object in the input scene, whereas the SDF-based classical JTC and binary JTC fail to achieve this.

Citation Download Citation

Ruikang K. Wang, Christopher R. Chatwin, and Lin Shang "Synthetic discriminant function fringe-adjusted joint transform correlator," Optical Engineering 34(10), (1 October 1995). https://doi.org/10.1117/12.210732

Published: 1 October 1995

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