tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File Exchange - type:functionUser-contributed code library2014-11-23T08:48:46-05:001581100tag:www.mathworks.com,2005:FileInfo/291542010-10-28T01:49:08Z2014-11-23T01:42:04ZA thin MATLAB wrapper for the Git source control systemUse this exactly as you would use the OS command-line Git, but from within MATLAB<p>Detailed documentation for this utility is available here:
<br /><a href="http://magpie.io/blog/2010/10/30/make-matlab-git-play-well-together/">http://magpie.io/blog/2010/10/30/make-matlab-git-play-well-together/</a></p>
<p>If you have modifications to this file that you'd like to share, I welcome them. Please follow the instructions on issuing a pull request at the main repo to do this:</p>
<p><a href="https://github.com/manur/MATLAB-git">https://github.com/manur/MATLAB-git</a></p>
<p>--
<br />A thin MATLAB wrapper for Git.</p>
<p> Short instructions:
<br /> Use this exactly as you would use the OS command-line verison of Git.</p>
<p> Long instructions are:
<br /> See: <a href="http://magpie.io/blog/2010/10/30/make-matlab-git-play-well-together/">http://magpie.io/blog/2010/10/30/make-matlab-git-play-well-together/</a></p>Manu Raghavanhttp://www.mathworks.com/matlabcentral/fileexchange/authors/113665MATLAB 7.11 (R2010b)MATLABGit:
http://git-scm.com/downloadfalsetag:www.mathworks.com,2005:FileInfo/220222008-11-07T05:54:22Z2014-11-22T07:20:14Zmatlab2tikzA script to convert MATLAB/Octave into TikZ figures for easy and consistent inclusion into LaTeX.<p>If you would like to see more information, follow the development, submit a bug, or contribute in any other way, please visit matlab2tikz's web page at <a href="https://github.com/nschloe/matlab2tikz">https://github.com/nschloe/matlab2tikz</a> .
<br />matlab2tikz supports the conversion of most MATLAB figures,
<br />including 2D and 3D plots. For plots constructed with third-
<br />party packages, your mileage may vary.
<br />The workflow is as follows.
<br /> 1. Place matlab2tikz in a directory where MATLAB can find it.
<br /> (the current directory, for example).
<br /> 2. Generate your plot in MATLAB.
<br /> 3. Invoke matlab2tikz by
<br /> >> matlab2tikz( 'myfile.tikz' );</p>
<p>The resulting file can be included into any LaTeX document (by \input{myfile.tikz}). Don't forget to add</p>
<p> \usepackage{pgfplots}</p>
<p>and optionally (as of Pgfplots 1.3)</p>
<p> \pgfplotsset{compat=newest}
<br /> \pgfplotsset{plot coordinates/math parser=false}</p>
<p>to the preamble of your LaTeX document.</p>
<p>To specify the dimension of the plot from within the LaTeX document, try</p>
<p> >> matlab2tikz('myfile.tikz', 'height', '\figureheight', 'width', '\figurewidth');</p>
<p>and in the LaTeX source</p>
<p> \newlength\figureheight
<br /> \newlength\figurewidth
<br /> \setlength\figureheight{4cm}
<br /> \setlength\figurewidth{6cm}
<br /> \input{myfile.tikz}</p>
<p>For decreasing the output TeX file size, try</p>
<p> cleanfigure;
<br /> matlab2tikz('myfile.tex');</p>
<p>and look at the parameter `floatFormat`.</p>Nico Schlömerhttp://www.mathworks.com/matlabcentral/fileexchange/authors/34666MATLAB 8.2 (R2013b)falsetag:www.mathworks.com,2005:FileInfo/482082014-10-21T09:35:41Z2014-11-22T07:20:10ZGIBBON: The Geometry and Image-Based Bioengineering add-On for MATLABGIBBON: The Geometry and Image-Based Bioengineering add-On for MATLAB<p>The Geometry and Image-Based Bioengineering add-On for MATLAB
<br />GIBBON is an open-source MATLAB toolbox by Kevin M. Moerman and includes an array of image and geometry visualization and processing tools and is interfaced with free open source software such as TetGen, for robust tetrahedral meshing, and FEBio for finite element analysis. The combination provides a highly flexible image-based modelling environment and enables advanced inverse finite element analysis.
<br />This can be considered a beta version. Documentation is still a work in progress. For installation instruction see <a href="http://www.gibboncode.org/installation/">http://www.gibboncode.org/installation/</a>
<br />Tested on Windows 7 64-bit and UBUNTU 14.04 64-bit with MATLAB R2014b. </p>
<p><a href="http://www.gibboncode.org">www.gibboncode.org</a></p>
<p>DOI: 10.5281/zenodo.12214
<br /><a href="https://zenodo.org/record/12214">https://zenodo.org/record/12214</a></p>
<p>A conference paper on the toolbox:</p>
<p>Moerman, K.M., A.J. Nederveen, and C.K. Simms, "Image Based Model Construction, Boundary Condition Specification and Inverse FEA Control: A Basic MATLAB Toolkit For FEBio", in Proceedings of the 11th International Symposium, Computer Methods in Biomechanics and Biomedical Engineering. 2013: Salt Lake City, Utah, USA.</p>Kevin Moermanhttp://www.mathworks.com/matlabcentral/fileexchange/authors/30817MATLAB 8.4 (R2014b)Image Processing ToolboxOptimization ToolboxStatistics ToolboxMATLABFEBio (www.febio.org)
TetGen (included)falsetag:www.mathworks.com,2005:FileInfo/470232014-06-21T11:40:25Z2014-11-22T07:01:02ZChebfunChebfun is an open-source package for numerical computation with functions to 15-digit accuracy<p>Chebfun is an open-source software system for numerical computing with functions. The mathematical basis is piecewise polynomial interpolation implemented with what we call “Chebyshev technology”. The foundations are described, with Chebfun examples, in the book Approximation Theory and Approximation Practice (L. N. Trefethen, SIAM 2013). Chebfun has extensive capabilities for dealing with linear and nonlinear differential and integral operators, and also includes continuous analogues of linear algebra notions like QR and singular value decomposition. The Chebfun2 extension works with functions of two variables defined on a rectangle in the x-y plane.</p>
<p>Most Chebfun commands are overloads of familiar MATLAB commands — for example sum(f) computes an integral, roots(f) finds zeros, and u = L\f solves a differential equation.</p>
<p>To get a sense of the breadth and power of Chebfun, a good place to start is by looking at our Examples (<a href="http://www.chebfun.org/examples/">http://www.chebfun.org/examples/</a>) or the introductory Guide (<a href="http://www.chebfun.org/docs/guide/">http://www.chebfun.org/docs/guide/</a>).</p>
<p>Please contact us with any questions/comments at <a href="mailto:help@chebfun.org">help@chebfun.org</a>.</p>Chebfun Teamhttp://www.mathworks.com/matlabcentral/fileexchange/authors/55471MATLAB 8.2 (R2013b)MATLAB23972falsetag:www.mathworks.com,2005:FileInfo/236292009-04-11T12:28:01Z2014-11-22T07:00:15Zexport_figExports figures nicely to a number of vector & bitmap formats.<p>This function saves a figure or single axes to one or more vector and/or bitmap file formats, and/or outputs a rasterized version to the workspace, with the following properties:
<br /> - Figure/axes reproduced as it appears on screen
<br /> - Cropped borders (optional)
<br /> - Embedded fonts (pdf only)
<br /> - Improved line and grid line styles
<br /> - Anti-aliased graphics (bitmap formats)
<br /> - Render images at native resolution (optional for bitmap formats)
<br /> - Transparent background supported (pdf, eps, png)
<br /> - Semi-transparent patch objects supported (png only)
<br /> - RGB, CMYK or grayscale output (CMYK only with pdf, eps, tiff)
<br /> - Variable image compression, including lossless (pdf, eps, jpg)
<br /> - Optionally append to file (pdf, tiff)
<br /> - Vector formats: pdf, eps
<br /> - Bitmap formats: png, tiff, jpg, bmp, export to workspace
<br />This function is especially suited to exporting figures for use in publications and presentations, because of the high quality and portability of media produced.
<br />Note that the background color and figure dimensions are reproduced (the latter approximately, and ignoring cropping & magnification) in the output file. For transparent background (and semi-transparent patch objects), use the -transparent option, and set the axes 'Color' property to 'none' where desired. Pdf, eps and png are the only file formats to support a transparent background, whilst the png format alone supports transparency of patch objects.
<br />When exporting to vector format (pdf & eps), and to bitmap using the painters renderer, this function requires that ghostscript is installed on your system. You can download this from:
<br /> <a href="http://www.ghostscript.com">http://www.ghostscript.com</a>
<br />When exporting to eps it additionally requires pdftops, from the Xpdf suite of functions. You can download this from:
<br /> <a href="http://www.foolabs.com/xpdf">http://www.foolabs.com/xpdf</a>
<br />Usage examples and tips can be found in the README at:
<br /><a href="https://github.com/ojwoodford/export_fig/blob/master/README.md">https://github.com/ojwoodford/export_fig/blob/master/README.md</a>
<br />When reporting bugs, please either use the 'Contact Author' link on my Author page, or raise an issue via GitHub. Please do not paste the error into the comments - I will not respond to these.</p>Oliver Woodfordhttp://www.mathworks.com/matlabcentral/fileexchange/authors/29192MATLAB 8.4 (R2014b)MATLABGhostscript, Xpdf1088915743179282097923604falsetag:www.mathworks.com,2005:FileInfo/341992011-12-14T07:16:07Z2014-11-22T04:44:56ZPseudo B-Mode Ultrasound Image SimulatorSimulate pseudo B-mode ultrasonic images with customized tissue echogenicity maps<p>fcnPseudoBmodeUltrasoundSimulator generates a simulated Pseudo B-Mode Ultrasound image given the tissue acoustic echogenicity model for the structure to be imaged. The simulated image is of same image matrix size as the input echogenicity map. Linear transducer array architecture is assumed for image formation. Image formed with assumption of wave propagating vertically along the echogenicity map.
<br />This implementation is based on method proposed in </p>
<p>[1] Yongjian Yu, Acton, S.T., "Speckle reducing anisotropic diffusion," IEEE Trans. Image Processing, vol. 11, no. 11, pp. 1260-1270, Nov 2002. [<a href="http://dx.doi.org/10.1109/TIP.2002.804276">http://dx.doi.org/10.1109/TIP.2002.804276</a>]</p>
<p>[2] J. C. Bambre and R. J. Dickinson, "Ultrasonic B-scanning: A computer simulation", Phys. Med. Biol., vol. 25, no. 3, pp. 463–479, 1980. [<a href="http://dx.doi.org/10.1088/0031-9155/25/3/006">http://dx.doi.org/10.1088/0031-9155/25/3/006</a>]</p>Debdoot Sheethttp://www.mathworks.com/matlabcentral/fileexchange/authors/207426MATLAB 7.13 (R2011b)MATLABImage Processing ToolboxSignal Processing Toolboxfalsetag:www.mathworks.com,2005:FileInfo/341722011-12-11T15:56:32Z2014-11-22T04:25:40ZBrightness Preserving Dynamic Fuzzy Histogram EqualizationBPDFHE employs fuzzy statistics of digital image to improve graylevel brightness preserved contrast <p>Brightness Preserving Dynamic Fuzzy Histogram Equalization(BPDFHE) proposes a novel modification of the brightness preserving dynamic histogram equalization technique to improve its brightness preserving and contrast enhancement abilities while reducing its computational complexity. This technique, called uses fuzzy statistics of digital images for their representation and processing. Representation and processing of images in the fuzzy domain enables the technique to handle the inexactness of gray level values in a better way, resulting in improved performance. Besides, the imprecision in gray levels is handled well by fuzzy statistics, fuzzy histogram, when computed with appropriate fuzzy membership function, does not have random fluctuations or missing intensity levels and is essentially smooth. This helps in obtaining its meaningful partitioning required for brightness preserving equalization.
<br />Details of the method are available in </p>
<p>D. Sheet, H. Garud, A. Suveer, J. Chatterjee and M. Mahadevappa, "Brightness Preserving Dynamic Fuzzy Histogram Equalization", IEEE Trans., Consumer Electronics, vol. 56, no. 4, pp. 2475 - 2480, Nov. 2010. [<a href="http://dx.doi.org/10.1109/TCE.2010.5681130">http://dx.doi.org/10.1109/TCE.2010.5681130</a>]</p>
<p>Implementation of the technique for grayscale images is outright. The function operates on non-sparce images of type uint8, uint16, int16, double and single.</p>
<p>Using BPDFHE for Color images can be done accordingly</p>
<p>rgbInputImage = imread('peppers.png');
<br />labInputImage = applycform(rgbInputImage,makecform('srgb2lab'));
<br />Lbpdfhe = fcnBPDFHE(labInputImage(:,:,1));
<br />labOutputImage = cat(3,Lbpdfhe,labInputImage(:,:,2),labInputImage(:,:,3));
<br />rgbOutputImage = applycform(labOutputImage,makecform('lab2srgb'));</p>
<p>Details of the technique for implementing BPDFHE on color images is detailed in </p>
<p>Garud, H. Sheet, D. Suveer, A. Karri, P.K. Ray, A.K. Mahadevappa, M. Chatterjee, J., "Brightness preserving contrast enhancement in digital pathology", Proc. ICIIP 2011. [<a href="http://dx.doi.org/10.1109/ICIIP.2011.6108964">http://dx.doi.org/10.1109/ICIIP.2011.6108964</a>]</p>Debdoot Sheethttp://www.mathworks.com/matlabcentral/fileexchange/authors/207426MATLAB 7.6 (R2008a)Image Processing ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/485362014-11-21T19:07:14Z2014-11-21T23:56:53ZBertiniLabToolbox for solving polynomial systems<p>BertiniLab is a MATLAB interface for Bertini, a general-purpose solver for systems of polynomial equations. Bertini can find isolated solutions and positive-dimensional solutions using homotopy continuation. The systems can be underdetermined, exactly determined or overdetermined. Bertini uses adaptive multiprecision and provides endgames to accurately compute singular roots. It also has efficient parameter continuation methods for families of systems that are related by one or more parameters.
<br />BertiniLab is a MATLAB interface that supports all features of Bertini version 1.4. The user can define a system of equations in several ways. They can write the equations as strings. They can create them as a Symbolic Toolbox array; if the user does not have this toolbox, a class POLYSYM is provided that emulates some of its features. The equations can also be generated using a MATLAB function, and matrix algebra is supported. The interface makes it easy to retrieve solutions, and BertiniLab can be tailored to specific applications by subclassing it.</p>Andrew Newellhttp://www.mathworks.com/matlabcentral/fileexchange/authors/73465MATLAB 8.0 (R2012b)MATLABBertini (Daniel J. Bates, Jonathan D. Hauenstein, Andrew J. Sommese, and Charles W. Wampler) can be obtained, free of charge, at https://bertini.nd.edu/.falsetag:www.mathworks.com,2005:FileInfo/485382014-11-21T22:10:59Z2014-11-21T22:10:59ZA Matlab function For Randomly Partitioning Date into Training, Validation and Testing DataA Matlab function For Randomly Partitioning Date into Training, Validation and Testing Data<p>This function randomly partitions data into training, validation and testing data using Cross Validation. Partitioning data in this manner is commonly used for determining the performance of algorithms with free parameters. Training data is commonly used to train the system, the optimum value for the free parameters is determined using validation data. Finally the results of the algorithm are determined using testing data. Matlab has a cross validation but I find it hard to use so I wrote my own. An example determining the optimum kernel with Support vector machines is used. Contact me if you have questions or suggestions</p>Joseph Santarcangelohttp://www.mathworks.com/matlabcentral/fileexchange/authors/477227MATLAB 7.14 (R2012a)falsetag:www.mathworks.com,2005:FileInfo/484662014-11-21T22:02:40Z2014-11-21T22:02:40ZText RecognizerEasily perform Optical Character Recognition (OCR) on your images!<p>Automatically perform OCR on your image. Specify language, ROI(s), character sets, etc... All supported capabilities of OCR are facilitated.
<br />Options include automatic pre-processing to improve results.</p>Brett Shoelsonhttp://www.mathworks.com/matlabcentral/fileexchange/authors/911MATLAB 8.4 (R2014b)Computer Vision System Toolboxfalse