Fast Anisotropic Edge Detection Using Gamma Correction in Color Images

Baptiste Magnier (1) , Philippe Montesinos (1) , Daniel Diep (1)

1 LGI2P - Laboratoire de Génie Informatique et Ingénierie de Production

In this paper we propose a new edge detector based on anisotropic linear filtering, local maximization and gamma correction. The novelty of this approach resides in the mixing of ideas coming both from directional recursive linear filtering and gamma correction. A peculiarity of our anisotropic edge detector is that it is based on the use of two elongated and oriented filters in two different directions. We show in this paper that unlike classical edge detection methods, gamma correction does not perturb the edge detection but enhances clearly the resulting contours obtained, especially in over-exposed or under-exposed areas of the image. Consequently, we propose a new edge operator enabling very precise detection of edge points involved in large structures. This detector has been tested successfully on various image types presenting difficult problems for classical edge detection methods.

Domaines: Traitement des images [eess.IV]

Baptiste Magnier, Philippe Montesinos, Daniel Diep. Fast Anisotropic Edge Detection Using Gamma Correction in Color Images. 7th International Symposium on Image and Signal Processing and Analysis (ISPA 2011), Sep 2011, Dubrovnik, Croatia. http://www.isispa.org/ispa11/. ⟨hal-00807802⟩