Title :
A New Edge Detection Method Based on Hausdorff Distance
Author :
Lu You ; Meng Qingxin ; Guo Jiangtao
Author_Institution :
Sch. of Comput. Sci. & Technol., China Univ. of Pet., Beijing, China
Abstract :
Most edge detection methods are based on first-order or second-order differential. These are local methods. Using Hausdorff distance to quantify the strength of the edge is a method with a holistic property. Firstly, down sample the image, and split the image into two sets. Secondly, get the feature image by assigning a value for each point using the scalar field map constructed by Hausdorff distance. Since the edge features have local properties, in this paper, we constructed a map which can get local feature images using sub image and combined them into a feature image. Finally we present a method to get the edge image by feature image. We experimentally verify the feasibility of this method.
Keywords :
edge detection; feature extraction; image sampling; Hausdorff distance; edge detection method; feature image; first-order differential; holistic property; image sampling; scalar field map; second-order differential; Bismuth; Equations; Feature extraction; Frequency modulation; Gray-scale; Image edge detection; Pattern recognition; Edge Detection; Feature Image; Hausdorff Distance; Image Processing;
Conference_Titel :
Digital Home (ICDH), 2014 5th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4799-4285-5
DOI :
10.1109/ICDH.2014.15