Title :
Geometrical shape recognition based on CDF extreme points analysis
Author_Institution :
Elektrik - Elektron. Muhendisligi Bolumu, Karadeniz Teknik Univ., Trabzon, Turkey
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;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7130116
