Open Source MATLAB Graphics Software

Octave Forge is a central location for collaborative development of packages for GNU Octave. The Octave Forge packages expand Octave's core functionality by providing field specific features via Octave's package system. See https://octave.sourceforge.io/packages.php for a list of all available packages. GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable. Refer to https://www.octave.org for more information.

Conway's Game of Life is generalized to a continuous domain. OpenGL and GLSL shaders are used for real-time 2D and 3D graphics. Time stepping is done via a real to complex FFT based convolution operation. There are also two deliberately simple test implementations in FreeBasic and Matlab. A 2D version on a sphere shows that it is really not dependent on the underlying grid.

Reconstruction and Visualization from a Single Projection (ReViSP) tool: a 3D volume rendering method we developed to reconstruct the 3D shape of multicellular spheroids, besides estimating the volume by counting the voxels (3D pixels) fully included in the 3D surface. ReViSP is written in MATLAB (The MathWorks, Inc., Massachusetts, USA) and the source code is freely provided. Requirements for running ReViSP from the source code: MATLAB 2020a and Image Processing Toolbox 11.1 or later versions. Please, when using this software, cite these articles: (a) F. Piccinini, et al., Cancer multicellular spheroids: Volume assessment from a single 2D projection. Computer Methods and Programs in Biomedicine, 118(2):95–106, 2015. (b) F. Piccinini, et al., Single-image based methods used for non-invasive volume estimation of cancer spheroids: a practical assessing approach based on entry-level equipment. Computer Methods and Programs in Biomedicine, 135:51-60, 2016.

The purpose of this program is to teach a computer to classify plants via their leaves. You just need to input the image of a leaf(acquired from scanner or camera), then the computer can tell you what kind of plant it is.

A Matlab toolbox for calibrating the Kinect Sensor. It provides functions to jointly calibrate the depth sensor with a color camera as well as to generate a depth map for the color image and reproject the points in metric coordinates.

Overhead Imagery Research Data Set (OIRDS) - an annotated data library & tools to aid in the development of computer vision algorithms

mVision library is a set of functions related with computer vision programmed in Matlab. Also include a couple of GUIs for test visually the functions.

Analysis Nuclei DAB (AND) Tool is a Graphical User Interface (GUI) to analyse microscopy images representing cells with nuclei stained using DAB dyes. The tool requires as input the original RGB images, and the FastRed, FastBlue, DAB channel, easily obtained using the Fiji function: "ImageJ" -> "Image" -> "Colour Deconvolution" -> "FastRed FastBlue DAB" Then, the tool first segment the nuclei using the FastBlue channel and the DAB channel, and then computes statistics by subdividing the sample in three regions according to the FastRed channel: a dark-red ROI, a light-pink ROI and a white ROI. ANDTool is written in MATLAB (The MathWorks, Inc., Massachusetts, USA) and the source code and standalone versions are here available for download. USER MANUAL: see the specific PDF available in the Files section. REQUIREMENTS: MATLAB R2017b and Image Processing Toolbox 10.1 or later versions. MAIN CONTACT: Filippo Piccinini (E-mail: filippo.piccinini85@gmail.com)

This package can be used for further development of package needs to deal with 3D geometrical relationship. It provides class for Vector, Point, Coordinate, transformations and also provides functions for dealing with relationships between them.

Algorithms based on Total Variation (TV) minimization are prevalent in image processing. They play a key role in a variety of applications such as image denoising, compressive sensing and inverse problems in general. In this work, we extend the TV dual framework that includes Chambolle's and Gilboa-Osher's projection algorithms for TV minimization. We use a flexible graph data representation that allows us to generalize the constraint on the projection variable. We show how this new formulation of the TV problem may be solved by means of fast parallel proximal algorithms. On denoising and deblurring examples, the proposed approach is shown not only to perform better than recent TV-based approaches, but also to perform well on arbitrary graphs instead of regular grids. The proposed method consequently applies to a variety of other inverse problems including image fusion and mesh filtering.

This application allows to generate graphics from data file in table format and a graphical configuration file XML..

F-Tracker3D is acronym of "fluorescent cell tracker in three-dimensions". It is a software tool designed to track fluorescent cells using time-lapse z-stacks of images acquired with a confocal or light-sheet microscope. First, each single cell is tracked in 2D by using the maximum intensity projections of the z-stacks and CellTracker, the free open source software available at: www.celltracker.website. Then, the 3D track of each cell is obtained analysing the z-stacks and looking for the z-plane with the maximum intensity value for the different x-y positions previously determined. F-Tracker3D is written in MATLAB (©, The MathWorks, Inc., Massachusetts, USA) and the source code is freely provided. Requirements: MATLAB 2015a and Image Processing Toolbox 9.2 or later versions.

Este proyecto presenta GraphUIS, una implementación de un periférico de video en un FPGA como un diseño modular caracterizado por no tener memoria dedicada. Se desarrolló como un proyecto académico en la Universidad Industrial de Santander.

Nowadays, the manual cell counting, performed directly by looking through the microscope’s oculars by using a tally counter and a hemocytometer, still is the gold standard method to count Live&Dead cells (Trypan Blue is typically used to stain the dead cells). However, performing the cell counting by tagging the cells in a steady image mosaic increases the reliability of the counts performed. Unfortunately, to build a mosaic of a hemocytometer's grid shows some problem due to the repeated patterns (i.e., the squared blocks of the grid). GridMos is an open-source software tool conceived to build an image mosaic of a hemocytometer's grid. It is optimized to build the mosaic starting from a sequence of overlapping images previously acquired. The Graphical User Interface (GUI) implemented makes GridMos a very user-friendly software tool. Requirements: MATLAB 2009b (32-bit) and Image Processing Toolbox 8.1 or later versions.

This MATLAB-based program enables analysis of AFM images. In particular, it allows the user to measure the volume of all distinguishable features in an image and to isolate and sort those particles. As the name implies, LAVA uses Lloyd's Algorithm, also known as k-means sorting, to identify a small set of volumes representative of the actual distribution of particle in the image. Although developed for determining feature volume, LAVA is also completely compatible with other types of image analysis, such as fluorescence intensity. Work is in progress to provide three-channel functionality, allowing comparison of relative intensity of red, green, and blue channels in multi-color images.

MORphological PHenotype Extraction (MORPHE) is a suite of automated image processing, visualization, and classification algorithms to facilitate the analysis of heritable and clonal red-to-green transitions that occurred during the growth of a colony.

Malimpa stands for MAtlab Library for IMage Processing and Analysis. It provides functions for 2D/3D grascale/color image creation, filtering, or measurement. It requires, and complements Matlab Image Processing Toolbox. Important notice: the project is now hosted in GitHub, https://github.com/dlegland/matImage

A set of Matlab toolboxes to perform signal and image processing.

The MatrixUser project is moving to GitHub, the latest version can be obtained from https://leoliuf.github.io/MatrixUser/ Most of the medical images (e.g. CT, MRI, PET, etc.) comprises multiple frames which represent slices, phases, timing etc. from the same imaging object. Those images can be saved as multidimensional matrices in Matlab thanks to Matlab's powerful support of multidimensional data representation. However, within Matlab, most of image manipulation functions are limited or tailored for processing two-dimensional matrix. The MatrixUser is a software package which features functions designed and optimized specifically for manipulating multidimensional real or complex data matrix. MatrixUser provides a nice graphical environment for easily performing image analysis tasks including multidimensional image display, matrix (image stack) processing and rendering etc. MatrixUser is a great lightweight tool for users who are working in image processing field under Matlab.

Land Mines detection using Image Processing

This is a program written in matlab to grade exams using Optical Mark Recognition. Samples of OMR sheets that are to be filled by students is also included. It supports rotation of up to 6 degrees as well as 180 degree rotation.

PMoz is a simple photomosaic generation code written in Matlab. It uses Directed Random Search and variant of the same (!!!!) to generate awesome photomosaic animations

This Matlab package implements machine learning algorithms described in the great textbook: Pattern Recognition and Machine Learning by C. Bishop (PRML). It is written purely in Matlab language. It is self-contained. There is no external dependency. This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). Many tricks for numerical stability are applied, such as computing probability in logrithm domain, square root matrix update to enforce matrix symmetry.

RandTree is a MatLab based tree simulator program where the algorithm is based on Honda's model. We have used probabilistic generation of branches in order to simulate visually realistic tree structures. This program is designed to generate branching structures with bifurcation branching pattern (sympodial branching). By changing the probabilities and branching angles, you can generate different shapes of trees.