Literature DB >> 22858935

Optical correlator based target detection, recognition, classification, and tracking.

Tariq Manzur1, John Zeller, Steve Serati.   

Abstract

A dedicated automatic target recognition and tracking optical correlator (OC) system using advanced processing technology has been developed. Rapidly cycling data-cubes with size, shape, and orientation are employed with software algorithms to isolate correlation peaks and enable tracking of targets in maritime environments with future track prediction. The method has been found superior to employing maximum average correlation height filters for which the correlation peak intensity drops off in proportion to the number of training images. The physical dimensions of the OC system may be reduced to as small as 2 in. × 2 in. × 3 in. (51 mm × 51 mm × 76 mm) by modifying and minimizing the OC components.

Year:  2012        PMID: 22858935     DOI: 10.1364/AO.51.004976

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  2 in total

Review 1.  Inference in artificial intelligence with deep optics and photonics.

Authors:  Gordon Wetzstein; Aydogan Ozcan; Sylvain Gigan; Shanhui Fan; Dirk Englund; Marin Soljačić; Cornelia Denz; David A B Miller; Demetri Psaltis
Journal:  Nature       Date:  2020-12-02       Impact factor: 49.962

2.  Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification.

Authors:  Julie Chang; Vincent Sitzmann; Xiong Dun; Wolfgang Heidrich; Gordon Wetzstein
Journal:  Sci Rep       Date:  2018-08-17       Impact factor: 4.379

  2 in total

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