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<html><head><title>Peter's Functions for Computer Vision</title><meta NAME="keywords" CONTENT="MATLAB,image processing,computer vision,phase congruency,edge detection,image enhancement, ransac"><meta NAME="description" CONTENT="MATLAB Functions for Computer Vision and Image Analysis. Functions include: Feature detection from Phase Congruency, Edge linking and segment fitting, Projective geometry, Image enhancement, and many others"><meta http-equiv="refresh"><meta http-equiv="Expires" content="Tue, 20 Aug 1996 14:25:27 GMT"></head><body bgcolor="#ffffff", marginwidth="20", marginheight="20"><center><h1>MATLAB and Octave Functions <br>for Computer Vision and Image Processing</h1></center><hr><table><tr><td width = 60%><h3><a href=http://www.csse.uwa.edu.au/~pk>Peter Kovesi</a></h3><H4>School of Computer Science & Software Engineering<br>The University of Western Australia <br>Crawley, Western Autralia. 6009</h4><td width=40%></table><hr>Please report any bugs and/or suggest enhancements to<br><img src="http://www.csse.uwa.edu.au/~pk/pkem14b.png"><p>Please note that I receive so many mail messages regarding thissite that I have difficulty responding to them all. I do not have the time to provide an on-line visionproblem solving service! However, I will endeavor to respond to mailthat directly concerns the use of individual functions.<p>Cheers,<br>Peter Kovesi<!--<img src="http://www.cs.uwa.edu.au/images/new.gif"> --><!--<img src="http://www.cs.uwa.edu.au/images/updated.gif"> --><br><br><br><hr>The complete set of these functions is available as a gzipped tar file <a href="../MatlabFns.tar.gz">MatlabFns.tar.gz</a> for Unix users.<br>Once you have untarred this file MATLAB users should remove the Octavesubdirectory from this package (or ensure it is not in your MATLABpath) to avoid problems.<!--, or as a zip file<a href="../MatlabFns.zip">MatlabFns.zip</a> for Windows users. --><p>Note that I develop my code under Mac OS X.<ul><li><a href=citesite.html>How to cite this site</a><li><a href=license.html>MIT License</a><li><a href=octaveinfo.html>Notes on using Octave</a> - almost all ofthese functions run under Octave. With the release of Octave 3 youhave a very viable alternative to MATLAB. </ul> <p> Legend for MATLAB/Octave compatibility <ul> <li type=square> Runs under MATLAB and Octave. <li type=circle> Only runs under MATLAB. <li type=disc> Not tested under Octave (yet). </ul><br><p>Can't find what you want here? Have a look at<br><a href=othersites.html>Other highly recommended Computer Vision software sites</a><a name="phasecong"></a><hr><h4>Feature detection via Phase Congruency</h4> <center><img align=top src=WWWImages/baboon.pc.gif> </center><br><ul><li type=square><a href=PhaseCongruency/phasecong.m>phasecong.m</a> Code forcalculating phase congruency in an image. Phase congruency is anillumination and contrast invariant measure of featuresignificance. It also correctly detects features at <i>all</i> kind ofphase angle, and not just step features with a phase angle of 0 or 180degrees. This function also returns a feature type image. Notehowever, this function is now only here for reference reasons, I nowrecommend that you use phasecong2 below.<li type=square><a href=PhaseCongruency/phasecong2.m>phasecong2.m</a> New phasecongruency code that combines edge and corner detection, and providesbetter localization. This function supersedes phasecong.m above.<li type=circle><a href=PhaseCongruency/dispfeat.m>dispfeat.m</a> Thisfunction provides visualisation and statistics of the differentfeature types found in an image by phasecong. Typically you will finda broad distribution of all feature types between step edges andlines. This function needs <ahref=LineSegments/edgelink.m>edgelink.m</a> (see below).<li type=square><a href=PhaseCongruency/odot.m>odot.m</a> Demonstratesthe actions of the 'Odot' and 'Oslash' operators on a 1D signal.These operators allow one to decompose and combine signals in a waythat is consistent with the Local Energy model of feature perception.<li><a href=PhaseCongruency/spatialgabor.m>spatialgabor.m</a> appliesa single oriented Gabor filter to an image.<center><table width=50%><tr><td><img align=top src=WWWImages/whalesm.jpg> <br> <td><center> <img align=topsrc=WWWImages/whalesmsym.jpg> <br>phase symmetry image</center></tr></table></center><li type=square><a href=PhaseCongruency/phasesym.m>phasesym.m</a> Code forcalculating phase symmetry. This can be used as a line and blobdetector. Phase symmetry is an illumination and contrast invariantmeasure of symmetry in an image. (A bright circle is not more'symmetric' than a grey circle as can be the case with some othermeasures!).<li type=square><ahref=PhaseCongruency/gaborconvolve.m>gaborconvolve.m</a> Code forconvolving an image with a bank of log-Gabor filters. Apre-processing step for texture analysis, feature detection andclassification, etc.<li type=circle><ahref=PhaseCongruency/plotgaborfilters.m>plotgaborfilters.m</a> Afunction for plotting log-Gabor filters. This function is useful forseeing what effect the various parameter settings have on theformation of a log-Gabor filter bankused in the functions above.<li type=square><a href=PhaseCongruency/monofilt.m>monofilt.m</a> Animplementation of Felsberg's monogenic filters. This function appliesa bank of monogenic filters to an image to obtain the 2D analytic signalover a number of scales. As in gaborconvolve this can be used as apre-processing step for texture analysis, feature detection andclassification, etc.<li><a href=PhaseCongruency/Docs/convexpl.html>An explanation</a> ofthe implementation of convolution with log-Gabor filters used in thefunctions above. </ul><p><b>References:</b><ul><li> Peter Kovesi, <a href="http://www.csse.uwa.edu.au/~pk/research/pkpapers/ai97.pdf"> "Symmetry and Asymmetry From Local Phase".</a> AI'97, Tenth Australian Joint Conference on Artificial Intelligence. 2 - 4 December 1997. Proceedings - Poster Papers. pp 185-190.<li> Peter Kovesi, <a href="http://mitpress.mit.edu/e-journals/Videre/001/v13.html"> "Image Features From Phase Congruency".</a> <i>Videre: A Journal of Computer Vision Research</i>. MIT Press. Volume 1, Number 3, Summer 1999.<li> Peter Kovesi, <a href="http://www.csse.uwa.edu.au/~pk/research/pkpapers/ACCV62.pdf"> "Edges Are Not Just Steps".</a> Proceedings of <em>ACCV2002 The Fifth Asian Conference on Computer Vision</em>, Melbourne Jan 22-25, 2002. pp 822-827. <li> Peter Kovesi, <a href="http://www.csse.uwa.edu.au/~pk/research/pkpapers/phasecorners.pdf"> "Phase Congruency Detects Corners and Edges".</a> <i> The Australian Pattern Recognition Society Conference: DICTA 2003. </i> December 2003. Sydney. pp 309-318.</ul><a name="spatial"></a><hr> <h4>Spatial feature detection</h4><ul><li type=square><a href=Spatial/canny.m>canny.m</a> Canny edgedetector incorporating modifications suggested by Fleck.<li type=square><a href=Spatial/harris.m>harris.m</a> Harris cornerdetector.<li type=square><a href=Spatial/fastradial.m>fastradial.m</a> Animplementation of Loy and Zelinski's fast radial featuredetector. </ul><p><b>Reference:</b><ul><li><a href=Spatial/Docs/Harris/index.html>Scanned images</a> of myphotocopy of Harris and Stephens' paper 'A Combined Corner and EdgeDetector'.</ul><a name="nonmax"></a><a name="hysthresh"></a><hr><h4>Non-maxima suppression and hysteresis thresholding</h4><center><img align=top src=WWWImages/baboon.pc.edge.gif></center><br> <ul><li type=square><a href=Spatial/nonmaxsup.m>nonmaxsup.m</a> Code forperforming non-maxima suppression for edge images.<li type=square><a href=Spatial/nonmaxsuppts.m>nonmaxsuppts.m</a> Codefor performing non-maxima suppression and thresholding of pointsgenerated by a feature/corner detector. It optionally returnssub-pixel feature locations.<li type=square> <a href=Spatial/hysthresh.m>hysthresh.m</a> code forperforming hysteresis thresholding. <li type=square> <a href=Spatial/smoothorient.m>smoothorient.m</a>applies smoothing to an orientation field which can be useful beforeapplying nonmaximal suppression.<li type=square> <a href=Spatial/adaptivethresh.m>adaptivethresh.m</a>an implementation of Wellner's adaptive thresholding method.</ul><a name="edgelink"></a><hr> <h4>Edge linking and line segment fitting</h4><center><table><tr><td><img align=top src=WWWImages/shapes.gif> <br> <center>image</center></td><td><img align=top src=WWWImages/shapese.gif> <br> <center>edges</center></td><td><img align=top src=WWWImages/shapeseim.gif> <br> <center>labeled edges</center></td><td><img align=top src=WWWImages/shapesseg.gif> <br> <center>fitted line segments</center></td></tr></table></center><br><ul><li><a href=LineSegments/edgelink.m>edgelink.m</a> edgelinking function that forms lists of connected edge points from abinary edge image. (Needs findendsjunctions and cleanedgelist below).<li><a href=LineSegments/drawedgelist.m>drawedgelist.m</a>plots out a set of edge lists generated by edgelink or lineseg.<li><a href=LineSegments/edgelist2image.m>edgelist2image.m</a>transfers edgelist data back into a 2D image array.<li><a href=LineSegments/lineseg.m>lineseg.m</a> formsstraight line segments fitted with a specified tolerance to the listsof connected edge points.<!-- Deprecated<li type=square><a href=LineSegments/mergeseg.m>mergeseg.m</a> is usedby lineseg.m to merge co-linear segments that may have been separatedin the edge linking process.<li type=square><a href=LineSegments/drawseg.m>drawseg.m</a> plots thefitted line segments.<li type=circle><a href=LineSegments/selectseg.m>selectseg.m</a>allows you to interactively select segments from an image.--><li type=square><a href=LineSegments/maxlinedev.m>maxlinedev.m</a> isalso used by lineseg.m to calculate deviations of the edge lists fromthe fitted segments.<li><a href=LineSegments/findendsjunctions.m>findendsjunctions.m</a>finds line junctions and endings in a line/edge image.<li><a href=LineSegments/cleanedgelist.m>cleanedgelist.m</a> cleans up aset of edge lists generated by edgelink or lineseg so that isolatededges and spurs that are shorter than a minimum length are removed.<li><a href=LineSegments/example/index.html>Example</a> of using thesefunctions above. </ul><a name="step2line"></a><hr> <h4>Test grating for edge detection</h4><center><table><tr><td><img align=top src=WWWImages/step2line.gif> <br><center>Test image</center></td><td><img align=top src=WWWImages/step2line.canny.gif> <br><center>Canny edge image</center></td><td><img align=top src=WWWImages/step2line.pc.gif> <br><center>Phase congruency</center></td><td><img align=top src=WWWImages/step2linecoded.gif> <br><center>Colour coded for feature type</center></td></table> </center> <br> <ul><li type=square><a href=PhaseCongruency/step2line.m>step2line.m</a>Generates a test image where the feature type changes from a step edgeto a line feature from top to bottom, while retaining perfect phasecongruency. This test image indicates the importance of phase?? 快捷鍵說明
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