Bayesian classification for the Statistical Hough transform

We have introduced the statistical Hough transform that extends the standard Hough transform by using a kernel mixture as a robust alternative to the 2 dimensional accumulator histogram. This work develops further this framework by proposing a Bayesian classification scheme to associate the spatial...

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Main Author: Dahyot, R.
Format: Conference Proceeding
Language:English
Subjects:
Bandwidth
Bayesian methods
Computer science
Discrete transforms
Educational institutions
Histograms
Image segmentation
Kernel
Robustness
Statistics
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description We have introduced the statistical Hough transform that extends the standard Hough transform by using a kernel mixture as a robust alternative to the 2 dimensional accumulator histogram. This work develops further this framework by proposing a Bayesian classification scheme to associate the spatial coordinates (x, y) to one particular class defined in the Hough space (¿, ¿). In a first step, we segment the Hough space into meaningful classes. Then using the inverse Radon transform, we backproject the different classes into the image space. We illustrate our approach on a synthetic image and on real images.
doi_str_mv 10.1109/ICPR.2008.4761109
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subjects Bandwidth
Bayesian methods
Computer science
Discrete transforms
Educational institutions
Histograms
Image segmentation
Kernel
Robustness
Statistics
title Bayesian classification for the Statistical Hough transform
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