Detail publikace

Interest Points as a Focus Measure in Multi-Spectral Imaging

Originální název

Interest Points as a Focus Measure in Multi-Spectral Imaging

Anglický název

Interest Points as a Focus Measure in Multi-Spectral Imaging

Jazyk

en

Originální abstrakt

A novel multi-spectral focus measure that is based on algorithms for interest point detection, particularly on the FAST (Features from Accelerated Segment Test), Fast Hessian and Harris-Laplace detector, is described in this paper. The proposed measure methods are compared with commonly used focus measure techniques like energy of image gradient, sum-modified Laplacian, Tenenbaum's algorithm or spatial frequency when testing their reliability and performance. The measures have been tested on a newly created database containing 420 images acquired in visible, near-infrared and thermal spectrum (7 objects in each spectrum). Algorithms based on the interest point detectors proved to be good focus measures satisfying all the requirements described in the paper, especially in thermal spectrum. It is shown that these algorithms outperformed all commonly used methods in thermal spectrum and therefore can serve as a new and more accurate focus measure.

Anglický abstrakt

A novel multi-spectral focus measure that is based on algorithms for interest point detection, particularly on the FAST (Features from Accelerated Segment Test), Fast Hessian and Harris-Laplace detector, is described in this paper. The proposed measure methods are compared with commonly used focus measure techniques like energy of image gradient, sum-modified Laplacian, Tenenbaum's algorithm or spatial frequency when testing their reliability and performance. The measures have been tested on a newly created database containing 420 images acquired in visible, near-infrared and thermal spectrum (7 objects in each spectrum). Algorithms based on the interest point detectors proved to be good focus measures satisfying all the requirements described in the paper, especially in thermal spectrum. It is shown that these algorithms outperformed all commonly used methods in thermal spectrum and therefore can serve as a new and more accurate focus measure.

BibTex


@article{BUT99720,
  author="Martin {Zukal} and Petr {Číka} and Jiří {Mekyska} and Zdeněk {Smékal}",
  title="Interest Points as a Focus Measure in Multi-Spectral Imaging",
  annote="A novel multi-spectral focus measure that is based on algorithms for interest point detection, particularly on the FAST (Features from Accelerated Segment Test), Fast Hessian and Harris-Laplace detector, is described in this paper. The proposed measure methods are compared with commonly used focus measure techniques like energy of image gradient, sum-modified Laplacian, Tenenbaum's algorithm or spatial frequency when testing their reliability and performance. The measures have been tested on a newly created database containing 420 images acquired in visible, near-infrared and thermal spectrum (7 objects in each spectrum). Algorithms based on the interest point detectors proved to be good focus measures satisfying all the requirements described in the paper, especially in thermal spectrum. It is shown that these algorithms outperformed all commonly used methods in thermal spectrum and therefore can serve as a new and more accurate focus measure.",
  chapter="99720",
  howpublished="electronic, physical medium",
  number="1",
  volume="2013",
  year="2013",
  month="april",
  pages="68--81",
  type="journal article"
}