An optimization method for edge-detector parameter tuning based on visual perception

Author

Teixeira, Flávio C A ; Bergen, Stuart W A ; Antoniou, Andreas

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Victoria, Victoria, BC, Canada

fYear

2009

fDate

23-26 Aug. 2009

Firstpage

660

Lastpage

665

Abstract

An optimization method for tuning the parameters of edge detection algorithms based on visual perception is proposed and applied to the Sobel, Laplacian of Gaussian (LoG), and Canny detectors. The method uses human visual quality perception to compare edge maps generated by different edge detector parameter values and iteratively reduces the parameter search space by means of a coordinate search. The method is applicable to any parameterized edge detector. Examples demonstrate that use of the Canny detector yields the most visually appealing edge maps. However, it requires 2.5 and 1.8 times the number of iterations required by the Sobel and LoG detectors, respectively.

Keywords

Gaussian processes; edge detection; optimisation; Canny detectors; Laplacian of Gaussian detectors; Sobel detectors; edge detection; human visual quality perception; optimization; parameter tuning; visual perception; Data mining; Detectors; Digital filters; Humans; Image edge detection; Image processing; Iterative algorithms; Laplace equations; Optimization methods; Visual perception;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Computers and Signal Processing, 2009. PacRim 2009. IEEE Pacific Rim Conference on

Conference_Location

Victoria, BC

Print_ISBN

978-1-4244-4560-8

Electronic_ISBN

978-1-4244-4561-5

Type

conf

DOI

10.1109/PACRIM.2009.5291293

Filename

5291293