An efficient method to evaluate the performance of edge detection techniques by a two-dimensional Semi-Markov model

Author

Dubinin, Dmitry ; Geringer, Viktor ; Kochegurov, Alexander ; Reif, Konrad

Author_Institution

Dept. of Radioelectron. & Data Protection, Tomsk State Univ. of Control Syst. & Radioelectron., Tomsk, Russia

fYear

2014

fDate

9-12 Dec. 2014

Firstpage

1

Lastpage

7

Abstract

The essay outlines one particular possibility of efficient evaluating the Performance of edge detector algorithms. Three generally known and published algorithms (Canny, Marr, Shen) were analysed by way of example. The analysis is based on two-dimensional signals created by means of two-dimensional Semi-Markov Model and subsequently provided with an additive Gaussian noise component. Five quality metrics allow an objective comparison of the algorithms.

Keywords

AWGN; Markov processes; edge detection; Canny algorithm; Marr algorithm; Shen algorithm; additive Gaussian noise component; edge detection techniques; edge detector algorithms; performance evaluation; quality metrics; two-dimensional semiMarkov model; two-dimensional signal analysis; Algorithm design and analysis; Computational modeling; Correlation; Image edge detection; Measurement; Noise; Vectors; Stochastic computer simulation; comparison of algorithms; edge detection; performance evaluation; two-dimensional Semi-Markov Model; two-dimensional renewal stream;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Control and Automation (CICA), 2014 IEEE Symposium on

Conference_Location

Orlando, FL

Type

conf

DOI

10.1109/CICA.2014.7013248

Filename

7013248