DocumentCode :
3168191
Title :
Fuzzy operators for quality evaluation in images edge detection
Author :
Perez-Ornelas, Felicitas ; Mendoza, Olivia ; Melin, Patricia ; Castro, Juan R.
Author_Institution :
Univ. Autonoma de Baja California, Tijuana, Mexico
fYear :
2013
fDate :
24-28 June 2013
Firstpage :
1182
Lastpage :
1187
Abstract :
Edge detection in an image is one of the most important tasks when working with image recognition, object identification, feature extraction, among others. There are different metrics to evaluate edges, such as Pratt, Jaccard, Dice but all these metrics binarize the image, and by performing this action information is lost from the image. This paper presents a new method that will allow the evaluation of the quality of the image of detected edges, using all the information of the image without binarization. This will be used for fuzzy sets as well as different operations with sets.
Keywords :
edge detection; feature extraction; fuzzy set theory; object detection; feature extraction; fuzzy operator; fuzzy sets; image edge detection; image quality evaluation; image recognition; object identification; Abstracts; Arrays; Detectors; Fuzzy sets; Image edge detection; Measurement; Saturn;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint
Conference_Location :
Edmonton, AB
Type :
conf
DOI :
10.1109/IFSA-NAFIPS.2013.6608568
Filename :
6608568
Link To Document :
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