DocumentCode :
1652456
Title :
The results of the investigation of the boaventura and gonzaga integrated performance evaluation method of edge detection based on the two-dimensional renewal stream
Author :
Geringer, V. ; Dubinin, D. ; Kochegurov, A. ; Reif, K.
Author_Institution :
Fac. of Eng., Baden-Wuerttemberg Cooperative State Univ., Friedrichshafen, Germany
fYear :
2015
Firstpage :
1
Lastpage :
4
Abstract :
The paper presents the results of the investigation of the I. Boaventura und A. Gonzaga integrated performance evaluation method of edge detection [1-2], obtained using the bundled software of stochastic simulation ≪CS sF≫ [3]. The methods and approaches of stochastic simulation were used in the experiments and the reference images were approximated with the two-dimensional renewal stream [4-7]. The performance of the outline drawing detection was evaluated by Boaventura und Gonzaga method for three algorithms of the edge detection (≪ Canny≫, ≪Marr-Hildreth≫ and ≪ISEF≫) under different levels of peak signal-to-noise ratio. The results of the investigation are presented as dependences of the estimate probability of the correct edge detection, the type 1 and 2 errors, on S/N ratio. The performance analysis of the above three algorithms for the images, produced on the basis of morphology type ≪A≫ and ≪F≫, is done based on the performed evaluation.
Keywords :
edge detection; probability; Boaventura and Gonzaga integrated performance evaluation method; edge detection; estimate probability; outline drawing detection; stochastic simulation; two-dimensional renewal stream; Algorithm design and analysis; Detectors; Image edge detection; Morphology; Performance evaluation; Software; Software algorithms; Two-dimensional renewal stream; comparison of algorithms; edge detection; performance evaluation; research on models; stochastic computer simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Circuits and Systems (ISSCS), 2015 International Symposium on
Conference_Location :
Iasi
Print_ISBN :
978-1-4673-7487-3
Type :
conf
DOI :
10.1109/ISSCS.2015.7203950
Filename :
7203950
Link To Document :
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