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 Region Growing Algorithm 

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A recursive region growing algorithm for 2D and 3D grayscale image sets with polygon and binary mask output. The main purpose of this function lies on clean and highly documented code.

Usage:
[P, J] = regionGrowing(cIM, initPos, thresVal, maxDist, tfMean, tfFillHoles, tfSimplify)

Inputs:
- cIM: 2D/3D grayscale matrix
- initPos: Coordinates for initial seed position
- thresVal: Absolute threshold level...



Segmentation by growing a region from user defined seed point, using intensity mean measure.
Simple and efficient (only one loop) example of "Region Growing" algorithm from a single seed point.

The region is iteratively...



An efficient algorithm for identification of strong polarity-inversion line (SPIL) on Solar Dynamic Observatory (SDO) Helioseismic and Magnetic Imager (HMI) magnetograms.

Detailed description will appear in the paper: Volobuev, D.M....



This software implements the fast continuous max-flow algorithm to 2D/3D multi-region image segmentation (Potts model). It provides three implementations: matlab, C and GPU (cuda based). All the source files are provided. So it is easy for you to...



This is an evolutionary algorithm that returns a random list of prime numbers. This code is highly inefficient for a reason. This algorithm is more of a proof of concept that if a prime was a heritable trait, it would not be a desired one.



This is a pure Python implementation of the rsync algorithm. On my desktop (3.0GHz dual core, 7200RPM), best case throughput for target file hash generation and delta generation is around 2.9MB/s. Absolute worst case scenario (no blocks in common)...



A-star (A*) Shortest Path Algorithm



Dijkstra shortest path algorithm.



Floyd-Steinberg dithering is an image dithering algorithm (see http://en.wikipedia.org/wiki/Floyd-Steinberg for more details). While the algorithm is mainly for image manipulation, I use it to create random locations for sensor networt devices.



This is a simple implementation of the famous LZW algorithm.



this algorithm predicts the received signal strength for the mobile user to avoid fluctuation in received signal strength during localization of the mobile user(finding mobile user's location)



NSGA-II is a very famous multi-objective optimization algorithm. I submitted an example previously and wanted to make this submission useful to others by creating it as a function. Even though this function is very specific to benchmark problems,...



Gravitational search algorithm (GSA) is an optimization algorithm based on the law of gravity and mass interactions.This algorithm is based on the Newtonian gravity: "Every particle in the universe attracts every other particle with a force...



The Jonker-Volgenant algorithm is much faster than the famous Hungarian algorithm for the Linear Assignment Problem (LAP). This Matlab implementation is modified from the original C++ code made by Roy Jonker, one of the inventors of the algorithm....



A flexible implementation of PSO algorithm with time-varying parameters. Algorithm is suitable for solving continuous optimization problems. Special care has been taken to enable flexibility of the algorthm with respect to its parameters and to...



findMIS is an heuristic algorithm for solving Maximum Independent Set problem (MIS).
An independent set of a graph is a subset of vertices in which no two vertices are
adjacent. Given a set of vertices, the maximum independent set...



We use the genetic algorithm (gatool) to determine the four parameters of the implicit Forst-Kalkwarf-Thodos Model. Predictions are in perfect agreement with data of vapour pressure of iodobenzene versus temperature for a temperature range from...



This is an extremely fast implementation of the famous Hungarian algorithm (aslo known as Munkres' algorithm). The new version (V2.2)is about 1.5 times faster than the old version (V2.1). It can solve a 1000 x 1000 problem in about 20 seconds in a...



This algorithm will accept a Latitude, Longitude and Altitude location as well as a specific universal coordinated time. It will use this information and calculate the position of the moon in a local coordinate frame (az and alt aka az and el).



This algorithm deal with multimodal optimization problems under constraints.