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Topic: Hough transform

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	PlanetMath: Hough transform
		The Hough transform is a general technique for identifying the locations and orientations of certain types of features in a digital image.
		The simplest form of the Hough transform is the Hough line transform.
		This is version 11 of Hough transform, born on 2002-04-28, modified 2006-08-06.
	planetmath.org /encyclopedia/HoughTransform.html (872 words)

	hough (Site not responding. Last check: 2007-10-14)
		After the transformation of drift chamber x-hits into lines by intersecting them with the z=0 plane, the x-wires were input into a Hough transformation.
		A hough transform is a general technique for translating a list of points into a particular space that make the extraction of correlations between points straight-forward.
		After the hough transform is utilized to determine the direction of the track through the x-wires, the x hits are associated with each track simply by looping over the hits and determining the closest hit to each track within each plane.
	skipper.physics.sunysb.edu /talks/snoopy/software/hough.htm (1418 words)

	Extraction of Range Information from Stereo Imagery using Hough Transforms
		The Hough transform produces a set of data in the (θ, d) plane with occasional “peaks” corresponding to the most prominent lines in the image.
		Since the Hough Transform gives a (hopefully) robust determination of linear features in the images, we postulate that there are correspondences between the two images in the stereo pair for at least some distance along the derived lines.
		The Hough transform would, it was hoped, extract line features in a very reliable fashion in the presence of contrast differential, point-of-view (occlusion) effects and other anomalies.
	filebox.vt.edu /users/crjones4/Hough_Stereo.htm (3923 words)

	HW 10: Hough Transform
		The Hough Transform is useful for segmenting images consisting of objects with known size and shape.
		In the Hough Transform a single pixel (or point) corresponds to an object (in this case a circle) in the original image space.
		Finally the Hough Transform (accumulator array or image) is searched for the maxima (which correspond to the desired objects).
	www.icaen.uiowa.edu /~roabel/dip/hw10.html (751 words)

	Sussex Computer Vision: TEACH VISION4 (Site not responding. Last check: 2007-10-14)
		The Hough transform is used in a variety of related methods for shape detection.
		Since the Hough transform is a global method, in that it integrates information over the entire image or region that it is given, it is not surprising that we need a way of focussing attention if it is to give information about features of limited size.
		The Hough transform is not restricted to detecting straight lines, though that is a common use.
	www.cogs.susx.ac.uk /users/davidy/teachvision/vision4.html (4312 words)

	Circular Hough Transform Demonstration
		The original image is shown on the left and the Hough transform of the image for the radius value entered is shown on the right.
		The transform is computed by taking the gradient of the original image (in this case, the Sobel gradient) and accumulating each non-zero point from the gradient image into every point that is one radius distance away from it.
		That way, edge points that lie along the outline of a circle of the given radius all contribute to the transform at the center of the circle, and so peaks in the transformed image correspond to the centers of circular features of the given size in the original image.
	www.markschulze.net /java/hough (380 words)

	GIS/EM4 - Discovering fault lines and fault planes from geological data using Hough Transform
		Developed by Paul Hough in 1962, the Hough Transform method has been used in the domain of artificial vision for the recognition of geometric features such as straight lines, circles, and ellipses from images.
		The goal of the adapted Hough Transform is to search a line (or a plane) in such a way that the number of data points passed by this line (or plane) is maximized in a three-dimensional data space.
		The selection of the parameters are based on several factors, such as the general knowledge of the behavior of fault lines and planes, the errors associated with the data, and the uncertainty in the identification of fault locations.
	www.colorado.edu /research/cires/banff/pubpapers/227/index.html (662 words)

	[No title]
		For a general introduction to the Hough transform, we refer to one of the other tutorials of CVOnline.
		In the original version of the Hough transform, the lines were given a slope-intercept parametric representation, i.e.
		It is exactly this special property that is exploited by the Cascaded Hough transform, which in fact boils down to applying several successive Hough transforms, with the output of one Hough transform used as input for the next Hough transform, switching back and forth between (x, y)-space and (a, b)-space.
	homes.esat.kuleuven.ac.be /~tuytelaa/CHT.html (1432 words)

	Amos Storkey - Demonstration - Hough Transform
		The Hough Transform is a global method for finding straight lines hidden in larger amounts of other data.
		To understand the Hough Transform, it is important to know what the Hough space is. Each point (d,T) in Hough space corresponds to a line at angle T and distance d from the origin in the original data space.
		The result of the Hough transform is a bright orange box on the right of the figure (the Hough space) which is the result of a large number of counts for that accumulator.
	www.anc.ed.ac.uk /~amos/hough.html (599 words)

	Hough
		The Hough module interface shows the parameter space image that represents the Hough transform in a visual manner.
		To use the Hough transform it is typical to first use an edge detection routine like the Sobel Edge.
		The Hough transform is VERY cpu intensive and not all the points need to be analyzed in order for a useful result to appear.
	www.roborealm.com /help/Hough.php (540 words)

	Hough Transform for Detecting Coins (Site not responding. Last check: 2007-10-14)
		Hough Transform computation - I first computed the radii of the coins present in the image.
		The two sequences are so processed because as the points reach the x (y)-axis, we get the same y(x)-value for different x(y)-values, for points lying on the circle corresponding to the hough transform.
		Detecting circles - Once the hough transform image for a particular radius is computed, it is adjusted to lie between 0 and 1 and thresholded, so as to leave only those points with high probability of being the centers.
	www.cc.gatech.edu /~kwatra/computer_vision/coins/coins.html (508 words)

	Image Transforms - Hough Transform
		The Hough transform is a technique which can be used to isolate features of a particular shape within an image.
		The main advantage of the Hough transform technique is that it is tolerant of gaps in feature boundary descriptions and is relatively unaffected by image noise.
		The generalized Hough transform is used when the shape of the feature that we wish to isolate does not have a simple analytic equation describing its boundary.
	homepages.inf.ed.ac.uk /rbf/HIPR2/hough.htm (2143 words)

	Image Transforms - Hough Transform (Site not responding. Last check: 2007-10-14)
		The Hough transform has many applications, as most manufactured parts (and many anatomical parts investigated in medical imagery) contain feature boundaries which can be described by regular curves or straight lines.
		The main advantage of the Hough transform is that it is tolerant of gaps in feature boundary descriptions and is relatively unaffected by image noise.
		The Hough transform space is now defined in terms of the possible positions of the shape in the image, i.e.
	cs-alb-pc3.massey.ac.nz /notes/59318/l11.html (1497 words)

	Hough Transforms
		Note that the Hough transform is invariant to rotation and translation.
		One useful property of the Hough transform is that the pixels which lie on the line need not all be contiguous.
		Indeed, this clearly shows that one disadvantage of the Hough transform method is that it gives an infinite line as expressed by the pair of m and c values, rather than a finite line segment with two well-defined endpoints.
	www.cs.cf.ac.uk /Dave/AI2/node196.html (752 words)

	HOUGH
		This function can be used to return either the Hough transform, which transforms each nonzero point in an image to a sinusoid in the Hough domain, or the Hough backprojection, where each point in the Hough domain is transformed to a straight line in the image.
		Usually, the Hough function is used with binary images, in which case H(q, r) gives the total number of sinusoids that cross at point (q, r), and hence, the total number of points making up the line in the original image.
		The Hough transform is not one-to-one: each point (x, y) is not mapped to a single (q, r).
	idlastro.gsfc.nasa.gov /idl_html_help/HOUGH.html (1192 words)

	Segmentation: The Hough Transform
		We can extend the Hough transform to find shapes of arbitrary complexity, so long as we can describe the shape with some fixed number of parameters.
		For the line-matching Hough Transform, the orientation of the line is one of the parameters.
		For the circular form of the transform, orientation is unnecessary.
	visl.technion.ac.il /labs/anat/12-Hough (1208 words)

	Hough Transform algorithm (Site not responding. Last check: 2007-10-14)
		The Hough Transform is a global method for finding straight lines (functions) hidden in larger amounts of other data.
		To understand the Hough Transform, it is important to know what the Hough space is.
		Each point (d,T) in Hough space corresponds to a line at angle T and distance d from the origin in the original data space.
	vision.cs.arizona.edu /nvs/research/image_analysis/hough.html (238 words)

	Fast Hough Transform
		In a Hough transform, each point in image space ``votes'' for that part of parameter space which describes structures which include the point.
		In the normal Hough transform approach, parameter space is bounded by setting lower and upper limits on the parameter values, and then divided into blocks in each direction, and an accumulator assigned to each block.
		The Hough transform proceeds with each point in image space being transformed to an region in parameter space as described in the previous paragraph.
	gandalf-library.sourceforge.net /tutorial/report/node134.html (287 words)

	Indexing - Hough Transform (Site not responding. Last check: 2007-10-14)
		The adoption of the Hough Transform was one of the most important steps in the automation of EBSD data collection.
		Some systems are rigid to the extent of matching image collection and binning to a fixed Hough, a processs which completely defeats the purpose of having an advanced, high resolution capable camera.
		In addition to the highly flexible "standard" Hough Transform, TSL has made two significant Advanced Hough Transform introductions: the Progressive Hough and the High Resolution Hough.
	www.edax.com /products/TSL/OIM/OIM-DC/indexing/hough/index.html (308 words)

	Advanced Hough Transform (Site not responding. Last check: 2007-10-14)
		In the traditional Hough transform, the width of the detected bands is strongly biased by the size of the convolution mask which is used to enhance the peaks in the Hough Transform.
		The Progressive Hough employs a different method for localizing the peaks in the Hough Transform that removes this bias.
		The user interface is designed so that the novice user can obtain good OIM results using the standard default Hough while at the same time providing the advanced user the flexibility to optimize the indexing procedure for a particular sample in terms of both speed and accuracy.
	www.edax.com /products/TSL/OIM/OIM-DC/indexing/hough/advanced.html (269 words)

	Untitled (Site not responding. Last check: 2007-10-14)
		Kesidis and N. Papamarkos, "On the inverse Hough transform", IEEE Trans.
		Kesidis and N. Papamarkos, " On the Inverse Hough transform and its application for edge detection and filtering", Proc.
		Kesidis and N. Papamarkos, "A window-based gray-scale inverse Hough transform algorithm and its applications on gray-scale line filtering", ICIP2001.
	ipml.ee.duth.gr /~papamark/Hough.html (178 words)

	Hough Transform
		The Hough transform [Hough59] is a standard tool in image analysis that allows recognition of global patterns in an image space by recognition of local patterns (ideally a point) in a transformed parameter space.
		Although the transform can be used in higher dimensions the main use is in two dimensions to find, e.g.
		In this form, the Hough transform is not basically different from the discrete Radon transform, typically used for reconstruction of three-dimensional images from two-dimensional projections.
	rkb.home.cern.ch /rkb/AN16pp/node122.html (367 words)

	MATLAB Central - Steve on Image Processing » Blog Archive » Showing image pixels associated with a Hough ...
		The Hough transform is used to detect line segments, typically in binary images.
		For the example we were looking at, some of the detected "line segments" didn't seem to correspond to line segments at all.
		So I think the Hough transform is not very useful for an image like this.
	blogs.mathworks.com /steve/?p=81 (1210 words)

	Hough Transformation (via CobWeb/3.1 planetlab2.netlab.uky.edu) (Site not responding. Last check: 2007-10-14)
		The Hough Transformation (HT) was invented in 1962 by P.V.C.Hough, and plays an important role in computerized image processing.
		In the end the highest valued accumulator cell is sought, its parameters represent the most probable line in the original image.
		These examples show why the HT is known to be the most robust method for shape detection because it tends to disregard noise and non-sought shapes.
	www.physik.uni-osnabrueck.de.cob-web.org:8888 /nonlinop/Hough/LineHough.html (493 words)

	Hough Circles (Site not responding. Last check: 2007-10-14)
		This plugin applies the Hough Transform for Circles to an 8-Bit image, shows the resulting Hough Space in a new window and marks the centers of the found circles.
		The Hough Transform implementation is based on an applet by Mark A. Schulze (http://www.markschulze.net)
		The "number of circles", X, entered by the user, will be used to choose the X most lightest points in the hough space.
	rsb.info.nih.gov /ij/plugins/hough-circles.html (171 words)

	The Hough Algorithm (Site not responding. Last check: 2007-10-14)
		The Hough algorithm is used to locate the unique
		If it is not known what defines a feature point, then it is reasonable to include every point in the Hough transform.
		If it is the randomized Hough transform that is being implemented, then a number of random points in the image will be chosen for examination.
	oldsite.vislab.usyd.edu.au /education/sc3/2000/hough/report/node3.html (164 words)

	Hough transform
		But because of the mismatch between the source parameters and the demodulated parameters we will observe a certain patterns in the time frequency diagram following the so called Hough transform master equation.
		It can be seen as the sum of several partial Hough maps constructed using just one periodogram.
		Since the Hough transform is performed on a set of spectra with discrete frequencies, if a peak on the spectrum appears at \nu it could correspond to any source with a demodulated frequency in a certain interval.
	www.aei.mpg.de /~sintes/HOUGH (933 words)

	Linear Hough - Square grating example (Site not responding. Last check: 2007-10-14)
		This example shows how to load an example image, take the Linear Hough Transform, and examine both the image and the transform with the Hough Tool.
		The image is this the size shown, and the Hough transform is larger.
		These steps set up the Hough Tool, so that clicking on the Hough Transform will mark the corresponding line in the image, and clicking on the image will mark the corresponding sinusoid in the Hough Transform.
	www.nist.gov /lispix/doc/TOOLS/hough-square-grating-example.htm (260 words)

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