39,700 research outputs found
A Comparative study of Arabic handwritten characters invariant feature
This paper is practically interested in the unchangeable feature of Arabic
handwritten character. It presents results of comparative study achieved on
certain features extraction techniques of handwritten character, based on Hough
transform, Fourier transform, Wavelet transform and Gabor Filter. Obtained
results show that Hough Transform and Gabor filter are insensible to the
rotation and translation, Fourier Transform is sensible to the rotation but
insensible to the translation, in contrast to Hough Transform and Gabor filter,
Wavelets Transform is sensitive to the rotation as well as to the translation
The Hough transform estimator
This article pursues a statistical study of the Hough transform, the
celebrated computer vision algorithm used to detect the presence of lines in a
noisy image. We first study asymptotic properties of the Hough transform
estimator, whose objective is to find the line that ``best'' fits a set of
planar points. In particular, we establish strong consistency and rates of
convergence, and characterize the limiting distribution of the Hough transform
estimator. While the convergence rates are seen to be slower than those found
in some standard regression methods, the Hough transform estimator is shown to
be more robust as measured by its breakdown point. We next study the Hough
transform in the context of the problem of detecting multiple lines. This is
addressed via the framework of excess mass functionals and modality testing.
Throughout, several numerical examples help illustrate various properties of
the estimator. Relations between the Hough transform and more mainstream
statistical paradigms and methods are discussed as well.Comment: Published at http://dx.doi.org/10.1214/009053604000000760 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Lens distortion correction by analysing the shape of patterns in Hough transform space : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Electronics and Computer Engineering at Massey University, Manawatu, New Zealand
Many low cost, wide angle lenses suffer from lens distortion, resulting from a radial variation in the lens magnification. As a result, straight lines, particularly those in the periphery, appear curved. The Hough transform is a commonly used linear feature detection technique within an image. In Hough transform space, straight lines and curved lines have different shapes of peaks. This thesis proposes a lens distortion correction method named SLDC based on analysing the shape of patterns in the Hough transform space. It works by reconstructing the distorted line from significant points on the smile-shaped Hough pattern. It then optimises the distortion parameter by mapping the reconstructed curved line into a straight line and minimising the RMSE. From both simulation and correcting real world images, the SLDC provides encouraging results
An Algebraic Approach to Hough Transforms
The main purpose of this paper is to lay the foundations of a general theory
which encompasses the features of the classical Hough transform and extend them
to general algebraic objects such as affine schemes. The main motivation comes
from problems of detection of special shapes in medical and astronomical
images. The classical Hough transform has been used mainly to detect simple
curves such as lines and circles. We generalize this notion using reduced
Groebner bases of flat families of affine schemes. To this end we introduce and
develop the theory of Hough regularity. The theory is highly effective and we
give some examples computed with CoCoA
An Extension to Hough Transform Based on Gradient Orientation
The Hough transform is one of the most common methods for line detection. In
this paper we propose a novel extension of the regular Hough transform. The
proposed extension combines the extension of the accumulator space and the
local gradient orientation resulting in clutter reduction and yielding more
prominent peaks, thus enabling better line identification. We demonstrate
benefits in applications such as visual quality inspection and rectangle
detection.Comment: Part of the Proceedings of the Croatian Computer Vision Workshop,
CCVW 2015, Year
Hierarchical Hough all-sky search for periodic gravitational waves in LIGO S5 data
We describe a new pipeline used to analyze the data from the fifth science
run (S5) of the LIGO detectors to search for continuous gravitational waves
from isolated spinning neutron stars. The method employed is based on the Hough
transform, which is a semi-coherent, computationally efficient, and robust
pattern recognition technique. The Hough transform is used to find signals in
the time-frequency plane of the data whose frequency evolution fits the pattern
produced by the Doppler shift imposed on the signal by the Earth's motion and
the pulsar's spin-down during the observation period. The main differences with
respect to previous Hough all-sky searches are described. These differences
include the use of a two-step hierarchical Hough search, analysis of
coincidences among the candidates produced in the first and second year of S5,
and veto strategies based on a test.Comment: 7 pages, 2 figures, Amaldi08 proceedings, submitted to JPC
Recognition of License Plates and Optical Nerve Pattern Detection Using Hough Transform
The global technique of detection of the features is Hough transform used in image processing, computer vision and image analysis. The detection of prominent line of the object under consideration is the main purpose of the Hough transform which is carried out by the process of voting. The first part of this work is the use of Hough transform as feature vector, tested on Indian license plate system, having font of UK standard and UK standard 3D, which has ten slots for characters and numbers.So tensub images are obtained.These sub images are fed to Hough transform and Hough peaks to extract the Hough peaks information. First two Hough peaks are taken into account for the recognition purposes. The edge detection along with image rotation is also used prior to the implementation of Hough transform in order to get the edges of the gray scale image. Further, the image rotation angle is varied; the superior results are taken under consideration. The second part of this work makes the use of Hough transform and Hough peaks, for examining the optical nerve patterns of eye. An available database for RIM-one is used to serve the purpose. The optical nerve pattern is unique for every human being and remains almost unchanged throughout the life time. So the purpose is to detect the change in the pattern report the abnormality, to make automatic system so capable that they can replace the experts of that field. For this detection purpose Hough Transform and Hough Peaks are used and the fact that these nerve patterns are unique in every sense is confirmed
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