Detail publikace

Effectect of Low-pass Filters as a Shi-Tomas Corner Detector´s Window Functions

Originální název

Effectect of Low-pass Filters as a Shi-Tomas Corner Detector´s Window Functions

Anglický název

Effectect of Low-pass Filters as a Shi-Tomas Corner Detector´s Window Functions

Jazyk

en

Originální abstrakt

The aim of this paper is to introduce an innovative way of using a low-pass spatial filter instead of window function of Shi–Tomasi corner detector, which is an enhancement of the Harris corner detector. The paper thus includes verification of the validity of this method on a reference image, and a comparison of different low-pass filters on test images. Particular spatial filters are linear smoothing filters mean filtering and Gaussian blur, and non-linear median filtering. The reason for this is to get an easy-to-implement algorithm for different architectures, such as a graphics card using shaders, which will allow fast processing of the input image even in real-time applications on less powerful devices, for example smartphones. This method can be applied not only to Shi–Tomasi corner detector, but also contains a formula for its use in the classic Harris corner detector. After a corresponding conversion of the evaluation function, the method can also be used for other variants of this corner detector, such as Noble detector.

Anglický abstrakt

The aim of this paper is to introduce an innovative way of using a low-pass spatial filter instead of window function of Shi–Tomasi corner detector, which is an enhancement of the Harris corner detector. The paper thus includes verification of the validity of this method on a reference image, and a comparison of different low-pass filters on test images. Particular spatial filters are linear smoothing filters mean filtering and Gaussian blur, and non-linear median filtering. The reason for this is to get an easy-to-implement algorithm for different architectures, such as a graphics card using shaders, which will allow fast processing of the input image even in real-time applications on less powerful devices, for example smartphones. This method can be applied not only to Shi–Tomasi corner detector, but also contains a formula for its use in the classic Harris corner detector. After a corresponding conversion of the evaluation function, the method can also be used for other variants of this corner detector, such as Noble detector.

BibTex


@inproceedings{BUT150920,
  author="Vladislav {Škorpil} and Jiří {Šťastný} and Luboš {Juránek}",
  title="Effectect of Low-pass Filters as a Shi-Tomas Corner Detector´s Window Functions",
  annote="The aim of this paper is to introduce an innovative way of using a low-pass spatial filter instead of window function of Shi–Tomasi corner detector, which is an enhancement of the Harris corner detector. The paper thus includes verification of the validity of this method on a reference image, and a comparison of different low-pass filters on test images. Particular spatial filters are linear smoothing filters mean filtering and Gaussian blur, and non-linear median filtering. The reason for this is to get an easy-to-implement algorithm for different architectures, such as a graphics card using shaders, which will allow fast processing of the input image even in real-time applications on less powerful devices, for example smartphones. This method can be applied not only to Shi–Tomasi corner detector, but also contains a formula for its use in the classic Harris corner detector.
After a corresponding conversion of the evaluation function, the method can also be used for other variants of this corner detector, such as Noble detector.",
  address="IEEE",
  booktitle="2018 41th International Conference on Telecommunication and Signal Processing",
  chapter="150920",
  doi="10.1109/TSP.2018.8441178",
  howpublished="online",
  institution="IEEE",
  year="2018",
  month="july",
  pages="623--626",
  publisher="IEEE",
  type="conference paper"
}