DocumentCode
714535
Title
Geometrical shape recognition based on CDF extreme points analysis
Author
Ozturk, Mehmet
Author_Institution
Elektrik - Elektron. Muhendisligi Bolumu, Karadeniz Teknik Univ., Trabzon, Turkey
fYear
2015
fDate
16-19 May 2015
Firstpage
1449
Lastpage
1452
Abstract
Automated shape recognition is a common problem which have been faced in computer vision applications. The feature(s) used to classify shapes should be chosen well for an accurate and fast way. Centroid distance function curve is a widely used feature in this field because of its quick and easy calculation properties. This study which is aimed to classify 2D convex geometric shapes based on the analysis of extreme points of the curve is proposed. The proposed method is robust to translation, rotation and scale of the objects.
Keywords
computer vision; geometry; shape recognition; 2D convex geometric shapes; CDF; automated shape recognition; centroid distance function curve; computer vision; extreme points analysis; geometrical shape recognition; Algorithm design and analysis; Computer vision; Computers; Pattern recognition; Robustness; Shape; Transforms; centroid distance function; computer vision; extreme point analysis; geometrical shape recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location
Malatya
Type
conf
DOI
10.1109/SIU.2015.7130116
Filename
7130116
Link To Document