Title :
Statistics of surface curvature estimates
Author :
Hilton, A. ; Illingworth, J. ; Windeatt, T.
Author_Institution :
Dept. of Electron. & Electr. Eng., Surrey Univ., Guildford, UK
Abstract :
Reliable curvature estimation is an important goal in image analysis to provide viewpoint independent cues for shape classification. This paper presents a model of the relationship between the variance of curvature estimates and the image noise. Agreement to within 10% is obtained for 3D range data. Previous models have only provided qualitative agreement with experimental observations. A perturbation error analysis is performed on the local least square surface fitting algorithm which is commonly used to obtain partial derivative estimates in the presence of noise
Keywords :
partial differential equations; 3D range data; image analysis; image noise; least square surface fitting algorithm; partial derivatives; perturbation error analysis; shape classification; surface curvature estimates; Error analysis; Image analysis; Image segmentation; Least squares approximation; Least squares methods; Noise shaping; Polynomials; Shape; Statistics; Surface fitting;
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
DOI :
10.1109/ICPR.1994.576222
