tag:www.mathworks.com,2005:/matlabcentral/fileexchange/feedMATLAB Central File Exchangeicon.pnglogo.pngMATLAB Central - File Exchange - type:Function product:"MATLAB" product:"Image Acquisition Toolbox"User-contributed code library2014-11-28T17:11:57-05:00271100tag:www.mathworks.com,2005:FileInfo/444002013-11-20T22:54:04Z2014-11-25T12:16:09ZTutorial and Toolbox on real-time optical flowCode with visualization and excercises. Camera supported<p>1) runMe.m
<br />(use arrow keys to interact with pattern)
<br />2) OpticalFlowTutorialPart1.pdf
<br />NOTE 1: This is a beta version. I would like to know about bugs so that I can improve this major update. We are working on a publication, so please check back for a proper reference if you plan on using this for your work.</p>
<p>Note 2: There are NO toolboxes required to run this. If it says differently below, ignore it.</p>
<p>Some of the material that was intended for use in parts 2 and 3 have ended up in proprietary software, so I hope those who were waiting for that will accept my apologies. To compensate, I am working hard to make part 1 (the only part) especially easy to use.</p>
<p><a href="http://islab.hh.se/mediawiki/index.php/Stefan_Karlsson/PersonalPage">http://islab.hh.se/mediawiki/index.php/Stefan_Karlsson/PersonalPage</a>
<br />A Quick view on applications:
<br /><a href="http://www.youtube.com/watch?v=h4umf0iCrFU">http://www.youtube.com/watch?v=h4umf0iCrFU</a></p>
<p>Get Started:
<br /><a href="http://youtu.be/u1jSwcVoFcM">http://youtu.be/u1jSwcVoFcM</a></p>Stefan Karlssonhttp://www.mathworks.com/matlabcentral/fileexchange/authors/174911MATLAB 8.1 (R2013a)MATLABSymbolic Math ToolboxControl System ToolboxImage Acquisition ToolboxComputer Vision System ToolboxNo toolboxes required. For webcam input you need the image acquistion toolbox OR Windows. Best performance with Image acquistion toolbox. If you dont have the image aquistion toolbox but do have windows, get the version on my page (URL above)falsetag:www.mathworks.com,2005:FileInfo/398512013-05-21T18:07:08Z2014-11-06T17:48:25ZAlgorithm Development With MATLABToolbox will all necessary files to support the Algorithm Development with MATLAB webinar<p>Copyright 2012-2014 The MathWorks, Inc.</p>Sumit Tandonhttp://www.mathworks.com/matlabcentral/fileexchange/authors/35517MATLAB 8.4 (R2014b)Image Acquisition ToolboxImage Processing ToolboxModel-Based Calibration ToolboxMATLABMATLAB Support Package for USB Webcams: http://www.mathworks.com/matlabcentral/fileexchange/45182-matlab-support-package-for-usb-webcamsfalsetag:www.mathworks.com,2005:FileInfo/477512014-09-05T08:51:05Z2014-09-05T20:04:35ZRanking based Face Recognition Face recognition finds its application in various modern technological advances.<p>Face Recognition is one of the most useful problems for Image Processing.
<br />• As our Face defines our Identity, we use are photo in all the official documents like, passport, license, adhar card, PAN card
<br />• Automating Face Recognition can help us automate a lot of activities like ticket booking for registered users, optional car parking, etc
<br />• It can help in reducing criminal activities
<br />Accurate and Efficient Face Recognition is boon for the technology.
<br />TRAINING SET DATABASE
<br />My courtesy to Amitabh Mukherjee of CSE,IIT Kanpur who has built up face database of male and females each person has 6 pose which makes our algorithm more robust in detecting faces. The dataset can be downloaded from this link. <a href="http://vis-www.cs.umass.edu/~vidit/AI/dbase.html">http://vis-www.cs.umass.edu/~vidit/AI/dbase.html</a> . In my algorithm I have taken only male faces and checked it with males faces only.
<br />IMPLEMENTATION AND DETAILS
<br />Algorithm used for face recognition is as follows : Based on PRINCIPAL COMPONENT ANALYSIS
<br />An orthogonal linear transformation that transforms the data to a new coordinate system such that the greatest variance by some projection of the data comes to lie on the first coordinate (called the first principal component), the second greatest variance on the second coordinate, and so on.(source: Wikipedia).
<br />• Take the dataset and store it in variables.
<br />• Calculate the eigen face vectors of dataset.
<br />• Calculate the average face vector.
<br />• Normalize all dataset by subtracting out average face vector from each dataset vector.
<br />• Calculate the eigen faces.
<br />• Input the unknown face.
<br />• Determine the distance between this unknown face vector and all eigen faces computed above.
<br />• Sort the distances and take out top 4 most distances and rank them in graphical user interface to give user a feel of ranking of images and make decision about which can be the best possible result among these 4 images for the given unknown image.
<br />PCA based approach is distance based approach which measures distance between images and computes rank of 4 images in my GUI corresponding to input GUI.
</p>Natrajanhttp://www.mathworks.com/matlabcentral/fileexchange/authors/448782MATLAB 7.10 (R2010a)Image Acquisition ToolboxImage Processing ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/475932014-09-04T15:39:56Z2014-09-04T18:38:18ZGetting Started AUVSIDocumentation and Examples for AUVSI Competitions<p>This code provides MATLAB and Simulink examples which participants in AUVSI competitions can use to learn how to program their autonomous vehicles.</p>
<p>Anyone who is interested in using MATLAB and/or Simulink on a PC to control their robotic platform will find this useful. </p>
<p>For AUVSI teams looking for more information, please see the following page:</p>
<p><a href="http://www.mathworks.com/academia/student-competitions/auvsi/">http://www.mathworks.com/academia/student-competitions/auvsi/</a>
</p>MathWorks Student Competitions Teamhttp://www.mathworks.com/matlabcentral/fileexchange/authors/473956MATLAB 8.3 (R2014a)Image Acquisition ToolboxImage Processing ToolboxSimulinkComputer Vision System ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/474222014-08-01T04:22:16Z2014-08-01T21:01:32ZMATLAB GUI for image type conversion(RGB to GRAYSCALE and RGB to BINARY)A real-time GUI for converting a image type of a snapshot from live video stream.<p>The file is interactive GUI for converting an image type of a snapshot captured from a live video stream. The GUI comprise of live video display and grayscale and binary image displays. There are 4 buttons, 1.videoinput,2.Preview,3.Grayscale image , 4. Bnary image.
<br />The videoinput button is used for initialising webcam of PC and Preview button for displaying the real-time webcam video in defined display window. Grayscale and binary image buttons are used for capturing the snapshot from webcam and converting it into grayscale and binary image respectively.</p>Rishabh Tharejahttp://www.mathworks.com/matlabcentral/fileexchange/authors/104341MATLAB 8.1 (R2013a)Image Acquisition ToolboxImage Processing ToolboxComputer Vision System ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/468792014-06-06T15:39:31Z2014-07-29T18:49:07ZGIGEACQ.mGiga ethernet Camera Acquisition<p>Set Up and Acquisition from a gigethernet video camera (in this case a Baumer Camera). GUI is coded in english but display is in French. At this point the program can save the pictures as frames for short movies or for longer movies in avi format. Some updates coming soon to record longer films at slower frame rate. If you have problem or advice to improve the program please let me know. But remember this is still work in progress so be kind with me ^^</p>Paul Elzierehttp://www.mathworks.com/matlabcentral/fileexchange/authors/397495MATLAB 8.3 (R2014a)Image Acquisition ToolboxMATLABgigevision packagefalsetag:www.mathworks.com,2005:FileInfo/471192014-07-02T15:51:35Z2014-07-02T22:15:55ZMouse pointer controlling using Laserproject enables the users to control presentation using laser as pointing device<p>The setup system consists of a computer connected to a projector and a webcam aimed at the presentation screen. The camera is used to detect the position of the pointing device (laser dot) on the screen, allowing the laser pointer to emulate the actions of a mouse such as moving the mouse pointer, clicking, scrolling etc. So the users need not remain near the computer, but can directly use laser pointer at a distance. Requires MATLAB 2012a(ver 7.14)</p>Chethanhttp://www.mathworks.com/matlabcentral/fileexchange/authors/482191MATLAB 7.14 (R2012a)Image Acquisition ToolboxImage Processing ToolboxComputer Vision System ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/466492014-05-17T17:39:33Z2014-05-19T21:28:56ZImage denoising using Evolutionary AlgorithmThis code performs Image denoising using Self Organizing Migration Algorithm (SOMA)<p>In this code we use SOMA and wavelet shrinkage to denoise images. Choice of traditional denoising methods require prior knowledge of kind of noise corrupting the image. Moreover, image denoising using Universal wavelet shrinkage is suited only for images corrupted with gaussian noise.
<br />In this code we use SOMA to find the parameters for wavelet shrinkage denoising such as choice of wavelet and thresholding values for various levels. Our algorithm is suited for various kinds of noise corrupting teh image such as gaussian, salt & pepper etc.
<br />The details of the algorithm can be found at
<br />Anupriya, Akash tayal, “Wavelet based Image Denoising using Self Organizing Migration Algorithm”,
<br />CiiT International Journal of Digital Image Processing, June 2012
<br /> </p>Anupriya Gognahttp://www.mathworks.com/matlabcentral/fileexchange/authors/423767MATLAB 8.1 (R2013a)Image Acquisition ToolboxImage Processing ToolboxWavelet ToolboxMATLABfalsetag:www.mathworks.com,2005:FileInfo/433972013-09-06T19:24:35Z2014-03-07T21:18:17ZDicom Operator - EsmeProcessEsmeProcess functions dicom image operation including viewing, drawing, writing and statistic.<p>EsmeProcess: The main program is functioning dicom operation with drawing/painting multiple Region Of Interest (ROI) on a given dicom image, saving/retrieving the results into/from the dicom header, computing various statistic required, and viewing 3D images. All the imroi tools (freehand, circle, rectangle, polygon) are used to define ROI region(s) with a sophisticated binary operation between them. The statistical functions include bar, plot and boxplot. Further functions are provided:
<br />SAVE:
<br /> - Save the ROI/painting into dicom header; save the image, statistic, mask and ROI in .dicom, .png, .mask and .xlsx formats correspondingly.
<br />READ:
<br /> - Read the ROI/painting from header and paint to the dicom image; also load.mask.
<br />EXPANSION:
<br /> - Expand the ROI based on the size defined in the option file.
<br />APPLY_TO_OTHERS:
<br /> - Apply the ROI to other images within the same dicom series either directly or by loading a .mask.
<br />STATISTIC:
<br /> - Calculate the mean, deviation and percentiles of aggregated ROI and display by plot, bar or boxplot in Statistic Menu. The aggregated ROI is computed based on an interactive binary operation. Each shape's histogram can be shown by right-click menu.
<br />OPTIONS:
<br /> - Load and configure the parameters. For example, the text object can be switched off by setting 'roitexton' parameter to zero in Options.
<br />INFOEDITOR:
<br /> - View, edit, anonymize and recover dicoms and headers
<br /> - View cross-section of 3D Images by scrolling up/down mouse wheel</p>
<p>Generated Information:
<br /> - Binary mask (.mask).
<br /> - Region Of Interest (.xlsx).
<br /> - Statistic of ROI (.png).
<br /> - Dicom images with painting history (.dicom).</p>
<p>This program is also a good example for people who intend to use some undocumented tools such as uitree, recent files menu and listbox context menu etc.</p>Jun Lihttp://www.mathworks.com/matlabcentral/fileexchange/authors/367028MATLAB 8.0 (R2012b)Image Acquisition ToolboxImage Processing ToolboxMATLABParallel Computing Toolbox (Optional)
Need Excel supportedfalsetag:www.mathworks.com,2005:FileInfo/456892014-02-25T19:53:35Z2014-02-25T22:18:54ZMatrix Difuse InterpolationCan correct some images with errors<p>That function can correct images when it have zones with wrong values.
<br />The method used is a lineal combination of lineal interpolation and difuse interpolation.
<br />The difuse interpolatio depends of the groups matrix centered on the pixels bounds.</p>David Pinedahttp://www.mathworks.com/matlabcentral/fileexchange/authors/436423MATLAB 8.2 (R2013b)Image Acquisition ToolboxImage Processing ToolboxMATLABA good computer ;)false