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Sensors (Basel). 2014 Feb 21;14(2):3690-701. doi: 10.3390/s140203690.

Feature point descriptors: infrared and visible spectra.

Sensors (Basel, Switzerland)

Pablo Ricaurte, Carmen Chilán, Cristhian A Aguilera-Carrasco, Boris X Vintimilla, Angel D Sappa

Affiliations

  1. CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL), Campus Gustavo Galindo, Km 30.5 vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador. [email protected].
  2. CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL), Campus Gustavo Galindo, Km 30.5 vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador. [email protected].
  3. Computer Science Department, Universitat Autònoma de Barcelona, Campus UAB, 08193 Bellaterra, Barcelona, Spain. [email protected].
  4. CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL), Campus Gustavo Galindo, Km 30.5 vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador. [email protected].
  5. CIDIS-FIEC, Escuela Superior Politécnica del Litoral (ESPOL), Campus Gustavo Galindo, Km 30.5 vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador. [email protected].

PMID: 24566634 PMCID: PMC3958214 DOI: 10.3390/s140203690

Abstract

This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given.

References

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  2. IEEE Trans Pattern Anal Mach Intell. 2005 Oct;27(10):1615-30 - PubMed
  3. IEEE Trans Pattern Anal Mach Intell. 2012 Jul;34(7):1281-98 - PubMed

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