Probabilistic Framework for the Characterization of Surfaces and Edges in Range Images, with Application to Edge Detection
Autor: | Antoine Lejeune, Marc Van Droogenbroeck, Jacques Verly |
---|---|
Rok vydání: | 2017 |
Předmět: |
Pixel
business.industry Applied Mathematics Probabilistic logic Pattern recognition Probability density function 02 engineering and technology 010501 environmental sciences 01 natural sciences Edge detection Range (mathematics) Computational Theory and Mathematics Artificial Intelligence Joint probability distribution 0202 electrical engineering electronic engineering information engineering Canny edge detector 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business Random variable Software 0105 earth and related environmental sciences Mathematics |
Zdroj: | IEEE transactions on pattern analysis and machine intelligence. 40(9) |
ISSN: | 1939-3539 |
Popis: | We develop a powerful probabilistic framework for the local characterization of surfaces and edges in range images. We use the geometrical nature of the data to derive an analytic expression for the joint probability density function (pdf) for the random variables used to model the ranges of a set of pixels in a local neighborhood of an image. We decompose this joint pdf by considering independently the cases where two real world points corresponding to two neighboring pixels are locally on the same real world surface or not. In particular, we show that this joint pdf is linked to the Voigt pdf and not to the Gaussian pdf as it is assumed in some applications. We apply our framework to edge detection and develop a locally adaptive algorithm that is based on a probabilistic decision rule. We show in an objective evaluation that this new edge detector performs better than prior art edge detectors. This proves the benefits of the probabilistic characterization of the local neighborhood as a tool to improve applications that involve range images. |
Databáze: | OpenAIRE |
Externí odkaz: |