We present a new method for detecting circles on digital images. This transform is called the circlet transform and can be seen as an extension of classical 1D wavelets in 2D: each basic element is a circle convolved by a 1D wavelet. In comparison with other circle-detector methods, mainly the Hough transform, the circlet transform takes into account the finite frequency aspect of the data: a c...

LFM signals are widely used in the fields of radar and communication etc., which make signals detection and parameters estimation a very important technology in multicomponent LFM signals. To solve the problems of error detection caused by the cross-terms in WVD-Hough methods and other modified WVD distribution methods, and low parameter estimation precision due to poor timefrequency concentrat...

This paper includes two novel techniques for skew estimation of binary document images. These algorithms are based on connected component analysis and Hough transform. Both these methods focus on reducing the amount of input data provided to Hough transform. In the first method, referred as word centroid approach, the centroids of selected words are used for skew detection. In the second method...

A new and eecient version of the Hough Transform for curve detection, the Randomized Hough Transform (RHT), has been recently suggested. The RHT selects n pixels from an edge image by random sampling to solve n parameters of a curve and then accumulates only one cell in a parameter space. In this paper, the RHT is related to other recent developments of the Hough Transform by experimental tests...

The generalized Hough transform is a method for extracting similar figures to the template figure in an image. The generalized Hough transform needs huge memory for the fourdimensional parameter space which represents positions, scales and rotation angles of objective figures and requires processor power for conversing addresses from an image space into the parameter space. The paper proposes a...

In this work we present two new algorithms for the detection of circles and ellipses which use the FHT algorithm as a basis: Fast Circle Hough Transform (FCHT) and Fast Ellipse Hough Transform (FEHT). The first stage of these two algorithms, devoted to obtaining the centers of the figures, is computationally the most costly. With the objective of improving the execution times of this stage it h...

The study of tree-rings is a common task in dendrology. Usually the rings deliver information about the age of the tree, historic climate conditions and forest densities. Many different techniques exist to perform the tree-ring detection, but they commonly are semi-automatic. The main idea of this work is to propose an automatic process for the tree-ring detection and compare it with a manual d...

Image recognition is one of the most important field in image processing that in recent decades had much attention .Due to expansion of related fields with image processing and various application of this science in machine vision, military science, geography, aerospace and artificial intelligence and lots of other aspects, out stand the importance of this subject.One of the most important aspe...

A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by him/her. Iris recognition (IR) is known to be the most reliable and accurate biometric identification system. The iris recognition system (IRS) consists of an automatic segmentation mechanism which is based on the Hough transform (HT). This paper presents a robust IRS i...

Systolic arrays belong to the class of pipelined array architectures where many identical processing elements (PE ́s) are interconnected locally so that data can be passed from all PE ́s to their respective neighbors synchronously and in parallel. In principle, all of them perform the same basic operation on their current operands in one clock cycle. At the University of Mannheim a systolic proce...