Object Signature Acquisition through Compressive Scanning

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7715)


In this paper we explore the utility of compressive sensing for object signature generation in the optical domain. We use laser scanning in the data acquisition stage to obtain a small (sub-Nyquist) number of points of an object’s boundary. This can be used to construct the signature, thereby enabling object identification, reconstruction, and, image data compression. We refer to this framework as compressive scanning of objects’ signatures. The main contributions of the paper are the following: 1) we use this framework to replace parts of the digital processing with optical processing, 2) the use of compressive scanning reduces laser data obtained and maintains high reconstruction accuracy, and 3) we show that using compressive sensing can lead to a reduction in the amount of stored data without significantly affecting the utility of this data for image recognition and image compression.


Digital Signal Processing Optical Signal Processing Compressive Sensing Shape Representation Object Signature Optical SuperComputing 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringUniversity of Texas at AustinAustinUSA
  2. 2.Department of Computer ScienceTexas State UniversitySan MarcosUSA
  3. 3.Department of Computer ScienceBen-Gurion University of the NegevBeer-ShevaIsrael

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