An iterative approach to Hough transform without re-voting

TL;DR

This paper introduces an iterative Hough transform method that efficiently models complex bone profiles in the human skeleton as connected piecewise algebraic curves, improving upon traditional single-curve fitting techniques.

Contribution

It presents a novel iterative approach to the Hough transform that avoids re-voting, enabling accurate piecewise curve fitting for complex bone profiles.

Findings

Efficiently describes bone profiles as connected piecewise curves.

Reduces computational complexity compared to traditional methods.

Improves accuracy in modeling complex skeletal shapes.

Abstract

Many bone shapes in the human skeleton are characterized by profiles that can be associated to equations of algebraic curves. Fixing the parameters in the curve equation, by means of a classical pattern recognition procedure like the Hough transform technique, it is then possible to associate an equation to a specific bone profile. However, most skeleton districts are more accurately described by piecewise defined curves. This paper utilizes an iterative approach of the Hough transform without re-voting, to provide an efficient procedure for describing the profile of a bone in the human skeleton as a collection of different but continuously attached curves.