Geometry of the Hough transforms with applications to synthetic data

04/04/2019
by   Mauro C. Beltrametti, et al.
0

In the framework of the Hough transform technique to detect curves in images, we provide a bound for the number of Hough transforms to be considered for a successful optimization of the accumulator function in the recognition algorithm. Such a bound is consequence of geometrical arguments. We also show the robustness of the results when applied to synthetic datasets strongly perturbed by noise. An algebraic approach, discussed in the appendix, leads to a better bound of theoretical interest in the exact case.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/17/2019

Algebraic geometry codes over abelian surfaces containing no absolutely irreducible curves of low genus

We provide a theoretical study of Algebraic Geometry codes constructed f...
research
01/06/2017

Analysis of Framelet Transforms on a Simplex

In this paper, we construct framelets associated with a sequence of quad...
research
08/08/2020

Partitioning signal classes using transport transforms for data analysis and machine learning

A relatively new set of transport-based transforms (CDT, R-CDT, LOT) hav...
research
07/07/2020

Incidences with curves in three dimensions

We study incidence problems involving points and curves in R^3. The curr...
research
09/17/2015

Learning from Synthetic Data Using a Stacked Multichannel Autoencoder

Learning from synthetic data has many important and practical applicatio...
research
09/28/2017

Recognition of feature curves on 3D shapes using an algebraic approach to Hough transforms

Feature curves are largely adopted to highlight shape features, such as ...
research
10/02/2010

A Microwave Imaging and Enhancement Technique from Noisy Synthetic Data

An inverse iterative algorithm for microwave imaging based on moment met...

Please sign up or login with your details

Forgot password? Click here to reset