Edge detection based on kernel density estimation

O. Pereira, Y. Garcés, R. Rodríguez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Edges of an image are considered a crucial type of information. These can be extracted by applying edge detectors with different methodology. Edge detection is a vital step in computer vision tasks, because it is an essential issue for pattern recognition and visual interpretation. In this paper, we propose a new method for edge detection in images, based on the estimation by kernel of the probability density function. In our algorithm, pixels in the image with minimum value of density function are labeled as edges. The boundary between two homogeneous regions is defined in two domains: the spatial/lattice domain and the range/color domain. Extensive experimental evaluations proved that our edge detection method is significantly a competitive algorithm.

Original languageEnglish (US)
Title of host publicationProceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017
EditorsHamid R. Arabnia, Leonidas Deligiannidis, Fernando G. Tinetti
PublisherCSREA Press
Pages123-128
Number of pages6
ISBN (Electronic)1601324642, 9781601324641
StatePublished - 1 Jan 2017
Event2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017 - Las Vegas, United States
Duration: 17 Jul 201720 Jul 2017

Publication series

NameProceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017

Conference

Conference2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017
CountryUnited States
CityLas Vegas
Period17/07/1720/07/17

Keywords

  • Edge Detection
  • Kernel Density Estimation
  • Probability Density Function

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  • Cite this

    Pereira, O., Garcés, Y., & Rodríguez, R. (2017). Edge detection based on kernel density estimation. In H. R. Arabnia, L. Deligiannidis, & F. G. Tinetti (Eds.), Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017 (pp. 123-128). (Proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2017). CSREA Press.