Hough transform can be used to detect parametric patterns, such as straight lines and circles, embedded in noisy images. The large amount of storage and computing power required by the Hough transform presents a problem in real-time applications. Multiresolution Hough transform (MHT) very efficient in reducing the computing and storage requirements. In this paper, we show the effectiveness of t...

This paper contains a brief literature survey of applications and improvements of the Hough transform, a description of the Hough transform and a few of its algorithms, and simulation examples of line and curve detection using the Hough transform.

A new branch of Hough Transform algorithms, called probabilistic Hough Transforms, has been actively developed in recent years. One of the rst was a new and eecient probabilistic version of the Hough Transform for curve detection, the Randomized Hough Transform (RHT). The RHT picks n pixels from an edge image by random sampling to solve n parameters of a curve and then accumulates only one cell...

We are not free from the side ef'fect caused by the digitization of the image also in Hough transform. Since Hough transform detects lines in the expression of the analog line equation, it is finally needed to extract digital line segments from the analog line equations. In this paper, we propose a new method DTHT(Digita1 Template Hough Transform) to detect digital line segments directly from t...

ÐIn this paper, an Inverse Hough Transform algorithm is proposed. This algorithm reconstructs correctly the original image, using only the data of the Hough Transform space and it is applicable to any binary image. As a first application, the Inverse Hough Transform algorithm is used for straight-line detection and filtering. The lines are detected not just as continuous straight lines, which i...

-In this paper we show how the use of qualitative features can enhance the performance of recognition and localization techniques, in particular, the Generalized Hough Transform. Qualitative features (i.e. scene features with qualitative attributes assigned to them) are shown to be effective in pruning the search space of possible scene interpretations and also reducing the number of spurious i...

The mathematical principles come from the "Maximum Likelihood Method" [2, 3], used in probability theory for the determination of distribution parameters from experimental data. The Maximum Likelihood analysis leads to the definition of the Probabilistic Hough Transform, which is a likelihood function. If certain assumptions are made about the error characteristics, the PHT is very close to con...

Hough transform is a well-known and popular algorithm for detecting lines in raster images. The standard Hough transform is rather slow to be usable in real-time, so different accelerated and approximated algorithms exist. This paper proposes a modified accumulation scheme for the Hough transform, which makes it suitable for computer systems with small but fast read-write memory – such as the t...

In this chapter, several advanced detection algorithms for Track-Before-Detect (TBD) procedures using the Hough Transform (HT) are proposed and studied. The detection algorithms are based on the scheme described in (Carlson et al., 1994) to use the Hough transform for simultaneous target detection and trajectory estimation. The concept described in (Carlson et al., 1994) accepts that a target m...

Hough-like methods (Implicite Shape Model, Hough forest, 9 ...) have been successfully applied in multiple computer vision fields like 10 object detection, tracking, skeleton extraction or human action detection. 11 However, these methods are known to generate false positives. To handle 12 this issue, several works like Max-Margin Hough Transform (MMHT) or 13 Implicit Shape Kernel (ISK) have re...