Title :
Using Geodesic Active Contours for motion-blurred images contour detection
Author :
Xu, Gang ; Shi, Lei
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing
Abstract :
Active contours model (snake) is a typical quantity dynamic contours model. Its main principle is to define a curve with energy in the area in which the researcher is interested, approaching the contours of the object through optimizing the energy function dynamically. Its biggest defect is that it can hardly handle the topological structure transformation when extracting the object contour. Geodesic active contours model (GAC), whose curve evolution equation doesnpsilat include any parameters that have no relation with the curvepsilas geometric structure, is based on the theory of curve evolution and level-set, so GAC can automatically process the topological structure transformation when extracting object contour. This paper proposes a new method of motion-blurred images contour detection. This method, which is based on the theory of GAC and the blurred image restoration, completely detects motion-blurred imagespsila contour. The theory and experimental analysis show that this new method has good effects.
Keywords :
edge detection; image restoration; geodesic active contours; image restoration; level-set; motion-blurred images contour detection; quantity dynamic contours model; topological structure transformation; Active contours; Biology computing; Cybernetics; Electronic mail; Evolution (biology); Image restoration; Machine learning; Military computing; Motion detection; Power engineering and energy; Curve evolution; Geodesic active contours; Level-Sets; Motion-blurred image restoration; topological transformation;
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
DOI :
10.1109/ICMLC.2008.4620929