tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File ExchangeUser-contributed code library2014-11-27T20:57:12-05:00224401100tag:www.mathworks.com,2005:FileInfo/485912014-11-28T01:31:52Z2014-11-28T01:32:56ZFace Recognition Biometric With Wavelet and Neural Network Matlab CodeFace Recognition Based on Wavelet and Neural Networks<p>Face Recognition [Wavelet and Neural Networks ] V2 : Simple and Effective Source Code for Face Recognition Based on Wavelet and Neural Networks.
<br />The code has been tested with AT&T database achieving an excellent recognition rate of 97.90% (40 classes, 5 training images and 5 test images for each class, hence there are 200 training images and 200 test images in total randomly selected and no overlap exists between the training and test images).See More :<a href="http://matlab-recognition-code.com/face-recognition-based-on-wavelet-and-neural-networks-matlab-code/">http://matlab-recognition-code.com/face-recognition-based-on-wavelet-and-neural-networks-matlab-code/</a></p>Hamdi Boukamchahttp://www.mathworks.com/matlabcentral/fileexchange/authors/516650MATLAB 7.13 (R2011b)falsetag:www.mathworks.com,2005:FileInfo/293032010-11-07T11:34:50Z2014-11-27T20:39:26ZDynamic Copula Toolbox 3.0Functions to estimate copula GARCH and copula Vine models.<p>Updates from version 2.0:
<br />1. The marginal GARCH models are estimated from the toolbox functions (without the use of the econometrics/GARCH toolbox of MATLAB).
<br />2. Hansen's Skew t distribution for the margins is supported.
<br />3. Asymptotic standard errors are computed (Godambe info. matrix)</p>Manthos Vogiatzoglouhttp://www.mathworks.com/matlabcentral/fileexchange/authors/30994MATLAB 7.7 (R2008b)Optimization ToolboxStatistics ToolboxMATLABEconometrics ToolboxSimulink Verification and Validationfalsetag:www.mathworks.com,2005:FileInfo/485902014-11-27T20:33:38Z2014-11-27T20:33:38ZGooding's State Vector-to-Orbital Elements AlgorithmMATLAB demo script and function that implements Gooding's method.<p>A MATLAB implementation of R. H. Gooding's method for converting an ECI state vector to classical orbital elements. Valid for elliptical and hyperbolic orbits. Reference: R. H. Gooding, "On Universal Elements, and Conversion Procedures To and From Position and Velocity", Celestial Mechanics 44 (1988), 283-298</p>David Eaglehttp://www.mathworks.com/matlabcentral/fileexchange/authors/30927MATLAB 8.0 (R2012b)falsetag:www.mathworks.com,2005:FileInfo/485092014-11-19T16:04:08Z2014-11-27T19:03:15ZComputational Geometry ToolboxConvex hull, mesh generation, Delaunay triangulation, Voronoi diagram and other algorithms.<p>In this submission, finite element mesh, Delaunay triangulations and Voronoi diagrams are generated through the use of the convex hull algorithm, which is implemented in an optimized way that maximizes speed and performance. The Delaynay triangulation and Voronoi diagram algorithms are essentially based on the convex hull algorithm. Information about the code and the ways to be used is shown in 'Theory of convex hulls, Delaunay triangulations and Voronoi diagrams'. The convex hull algorithm is applied by the function 'convhull_nd', the Delaunay triangulation by the function 'delaunay_nd' and the Voronoi diagram by the function 'voronoi_nd'. All functions included in this package can be used for any dimension n. The use of the three aforementioned functions is illustrated by many examples, included in the file 'Contents'.
<br />The functions included in this submission can be used for the generation of finite element and boundary element meshes, which are utilized for discretization of various media, structural or not, to be numerically analysed.
<br />Apart from this, they can be used to solve various problems of computational geometry, such as:
<br />- convex hulls
<br />- intersections
<br />- triangulation and partitioning
<br />- line arrangements and duality
<br />- Voronoi diagrams and Delaunay triangulations
<br />- Point in polygon, etc.
<br />It has to be noted that most of these problems (many of which are included in this package as solved examples) are solved using essentially the convex hull algorithm.
<br />References:
<br />[1] The Quickhull Algorithm for Convex Hull, C. Bradford Barber, David P. Dobkin and Hannu Huhdanpaa, Geometry Center Technical Report GCG53, July 30, 1993.
<br />[2] Voronoi Diagrams from Convex Hulls, Kevin Q. Brown, Information Processing Letters, Vol.9, No.5, December 16, 1979
<br />[3] Voronoi Diagrams and Arrangements, Herbert Edelsbrunner and Raimund Seidel, Discrete & Computational Geometry 1:25-44, 1986</p>George Papazafeiropouloshttp://www.mathworks.com/matlabcentral/fileexchange/authors/105783MATLAB 8.0 (R2012b)MATLABfalsetag:www.mathworks.com,2005:FileInfo/479332014-09-26T18:59:11Z2014-11-27T18:52:18ZAutomatic detection of eyes,nose and mouth in an image using inbuilt matlab functionsUses vision toolbox<p>Uses vision toolbox</p>Lakshmihttp://www.mathworks.com/matlabcentral/fileexchange/authors/506945MATLAB 8.1 (R2013a)falsetag:www.mathworks.com,2005:FileInfo/485892014-11-27T17:23:21Z2014-11-27T17:23:21ZFibonacci SequenceThis code will generate a Fibonacci sequence<p>Fibonacci</p>Davidhttp://www.mathworks.com/matlabcentral/fileexchange/authors/518117MATLAB 8.3 (R2014a)falsetag:www.mathworks.com,2005:FileInfo/468432014-06-03T18:16:33Z2014-11-27T15:42:04ZDynamical Systems with Applications using MATLAB 2eMATLAB, Simulink and MuPAD files to accompany the second edition of the book.<p>"Dynamical Systems with Applications using MATLAB 2nd Edition" covers standard material for an introduction to dynamical systems theory. The text deals with both discrete and continuous systems. There are applications in computing, mechanical systems, chemical kinetics, electric circuits, interacting species, economics, nonlinear optics, biology, neural networks and materials science, for example. These MATLAB programs have been written to supplement the textbook, and give the reader a real hands-on experience. The text is aimed at senior undergraduates, graduate students, and working scientists in industry. Table of Contents of the book, mock exam papers and MATLAB index file can be found in Lynch_R2014b.zip.</p>Stephen Lynchhttp://www.mathworks.com/matlabcentral/fileexchange/authors/6536MATLAB 8.4 (R2014b)Image Processing ToolboxSimulinkSymbolic Math ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/485882014-11-27T15:15:52Z2014-11-27T15:15:52ZMulti-exposure and Multi-focus Image Fusion in Gradient DomainA toolbox for fusion of multi-exposure and multi-focus images<p>This toolbox can be used for fusion of multi-exposure as well as multi-focus images, and color as well as grayscale images. A gradient domain method of fusion has been incorporated.
<br />We recommend to go through the ReadMe.pdf file in this submission to have a better idea of the codes. More details regarding the working of the codes and the algorithm behind it, please refer to the following:</p>
<p>[1] Sujoy Paul, Ioana S. Sevcenco, Panajotis Agathoklis, "Multi-exposure and Multi-focus Image Fusion in Gradient Domain", (Submitted to Journal of Circuits, Systems and Computers)</p>
<p>[2] I.S. Sevcenco, P.J. Hampton, P. Agathoklis, "A wavelet based method for image reconstruction from
<br />gradient data with applications", Multidimensional Systems and Signal Processing, November 2013</p>Sujoy Paulhttp://www.mathworks.com/matlabcentral/fileexchange/authors/492399MATLAB 8.3 (R2014a)MATLAB48066falsetag:www.mathworks.com,2005:FileInfo/485872014-11-27T12:51:11Z2014-11-27T12:54:32ZLOSIB (Local Oriented Statistics Information Booster) for texture retrieval)Function based on the method published in ICPR 2014 LOSIB for texture retrieval.<p>Function for texture retrieval very useful in combination with other descriptors such as LBP, Wavelet features, etc.
<br />This zip contains two .m files: 1. getLosib.m (LOSIB method function) 2. LOSIBExample.m (Example of usage) and three test images test[1:3].jpg</p>
<p>If you use this code, please cite us:
<br />García-Olalla, O., E. Alegre, L. Fernández-Robles, and V. González-Castro, "Local Oriented Statistics Information Booster (LOSIB) for Texture Classification", International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 2014</p>
<p>For any doubt, contact me at <a href="mailto:ogaro@unileon.es">ogaro@unileon.es</a>
<br />Thank you.</p>Oscar García-Olallahttp://www.mathworks.com/matlabcentral/fileexchange/authors/529372MATLAB 8.3 (R2014a)Image Processing ToolboxMATLAB36484falsetag:www.mathworks.com,2005:FileInfo/485862014-11-27T12:24:41Z2014-11-27T12:25:09ZhslcolormapGenerate pleasing HSL colormaps easily.<p>Generate hue-saturation-lightness colormaps
<br />
<br /> USAGE: hslcolormap(N,H,S,L)
<br />
<br /> INPUTS:
<br /> N: number of colors in colormap.
<br /> H: hue stops (optional)
<br /> S: saturation stops (optional)
<br /> L: Lightness stops (optional)
<br />
<br />
<br /> EXAMPLE:
<br /> surf(peaks(200),'edgecolor','none');
<br /> cmap=hslcolormap(300,[.7 1.2 1],1,[0 1]);
<br /> colormap(cmap)
<br />
<br />
<br />
<br /> (c) Aslak Grinsted 2014</p>Aslak Grinstedhttp://www.mathworks.com/matlabcentral/fileexchange/authors/131455MATLAB 8.4 (R2014b)20292false