K means clustering for Image Compression by Vinay Kumar Tadepalli

K-means clustering is a popular vector quantization method for data compression. (image processing, demo, mathematics)

Kmeans_Pre_Post.m

kmeans_clustering.m

Image_kmeans_main.m

Gap statistics by Alessandro Crimi

Algorithm for cluster validity index, R. Tibshirani et al. 2001 (cluster, validity index, kmeans)

gap_statistics(data, num_clusters, num_reference_bootstraps...

test_gap_statistics(test_datas)

k-means++ by Laurent S

Cluster multivariate data using the k-means++ algorithm. (clustering, kmeans, data mining)

kmeans(X,k)

Fast K-means clustering by Sebastien PARIS

Fast mex K-means clustering algorithm with possibility of K-mean++ initialization. (statistics, image processing, mathematics)

test_yael_kmeans

gene_mvgm(d , K , sig)

mexme_yael_kmeans(options)

Improved Nystrom Kernel Low-rank Approximation by Kai

efficient, self-complete implementation of improved Nystrom low-rank approximation (machine learning, matrix lowrank approx..., manifold learning and...)

INys(kernel,data, m, s);

INys_KPCA(data, kernel, m);

INys_MDS(data, m);

A Fast Image Segmentation using Delaunay Triangulation (Revisited) by Abbas Cheddad

This is a tuned version of the old post on Delaunay-based image segmentation. (delaunay triangulatio..., image segmentation, cell segmentation)

DSNew.m

[Segmented Clusters]=DSIterate(Segmented,B,C,D)

Customized K-Means by Nirmal

Customized K-means where you can choose different initial cluster centroid. (kmeans, clustering)

[class,centroid,counter]=MyKMeans(data,k,option,init_centro...

k-means clustering algorithm by Craig

Performs one step of the k-means clustering algorithm (algorithm, images, average)

kmean(img,means)

Example.m

K-subspaces by Masayuki Tanaka

K-subspaces provides the k-means like clustering. (statistics, mathematics, image processing)

inpnormsubspaces(SS,X)

inpsubspaces(SS, X)

ksubspaces(X,k,dim,SS,iter,ep)

clusterData by Brett Shoelson

Clusters an MxN array of data into an unspecified number (P) of bins. (data analysis, group data, cluster)

clusterData(data, sensitivity)

k-means intra cluster measure by ps

to find the cluster validation in k-means by intra cluster measure coding in matlab (data mining)

intra.m

EM algorithm for Gaussian mixture model by Mo Chen

EM algorithm for Gaussian mixture. Works on arbitray dimensions with high speed and precision. (em, clustering, gmm)

emgm(X, init)

logsumexp(x, dim)

spread(X, label)

K-medoids by Mo Chen

K-medoids clustering algorithm (kmedoids, clustering, kmeans)

kmedoids(X,k)

spread(X, label)

Spherical K-means by Mo Chen

A kmeans like clustering algorithm to cluster data on a unit sphere. (clustering)

spkmeans(X, init)

K-means++: kmeans algorithm with smart seeding by Mo Chen

This is an implementation of the paper k-means++: the advantages of careful seeding. (clustering, kmeans, data analysis)

kmeanspp(X, k)

spread(X, label)

Kernel k-means by Mo Chen

kernel k-means algorithm (kernel, kmeans, clustering)

knkmeans(K,init)

spread(X, label)

Nonlinear Relaxation Labeling for Image Processing by Anton Semechko

Improve spatial coherence of a 2D monochromatic/multispectral image using probabilistic relaxation (nonlinear relaxation ..., relaxation labeling, relaxation labelling)

MyKmeans.m

RelaxLabel2D_demo1

RelaxLabel2D_demo2

image segmentation with EM algorithm by Rongwen Lu

To implement EM algorithm with Gaussian mixed model and to apply it to the image segmentation (em algorithm, gaussian mixed model, image segmentation)

[maskOut]=kGaussian_color_EM(imageFile,k)

The Spherical K-means algorithm by Xuan Vinh Nguyen

Clustering on the hypersphere with the Spherical K-means algorithm (kmeans, spherical kmeans, clustering)

[best_x,best_f,best_membership,empty,loop]=SPKmeans(a,K,n_r...

b=normalize_norm(a)

b=normalize_norm_mean(a)

Software implementations of DC by qi zhang

advantage of speed compared with HAC & a stable and effective algorithm (data competition, clustering algorithm, data mining)

[new_center,cl]=update_centers(SD,II,E,K,num,center)

evalf(trueclass,cl,x,sfct)

similarity_euclid(data)

Iris data set clustering by Yella

Iris data set clustering (4d plot, data import, optimization)

dataclustering.m

Software implementations of PBKM by qi zhang

advantage of speed & performance appears under large number of clusters (clustering, large number of clust..., clustering algorithm)

IDXA=cut(n,IDX);

IDXA=divKMS(x,K);

T=cengci(x,K);

Two-way repeated measures ANOVA by Aaron Schurger

Two-way repeated measures ANOVA, for designs with two within-subjects variables. (statistics, probability, repeatedmeasures)

rm_anova2(Y,S,F1,F2,FACTNAMES)

Allstats by Francisco de Castro

Many statistics of a vector or matrix (statistics, mean, mode)

allstats(A,varargin)

color Image Segmentation by Athi

Segments a color image into regions. (clustering, segmentation, image segmentation)

colImgSeg(inImg, nBins, winSize, nClass)

SampleUsage.m

Color Quantization by Athi

This program reduces the number of colors present in a true color image (or indexed color image). (quantization, image processing, color reduction)

writeCSV(out_map, OutCSVName)

KMeansColorReduction.m

Fast K-means by Tim Benham

Fast K-means implementation with optional weights and K-means++ style seeding. (clustering, kmeans, weighted kmeans)

fkmeans(X, k, options)

K-means image segmentation by Pablo Fonseca

K-means image segmentation based on histogram to reduce memory usage which is constant for any size. (clustering, kmeans, image)

kmeansclustering(im, k)

Point Pattern Matching Algorithm for Hand Gesture / American Sign Language (ASL) Recognition by Caglar Arslan

A demonstration of American Sign Language recognition by using a Point Pattern Matching Algorithm. (american sign languag..., computer vision, pattern recognition)

Selecteds=findMax(results,depth);

appendimages(image1, image2)

hgr(input);

imcensor by Sean de

GUI to censor parts of an image (gui, censor, image)

imcensor(I)

Neuro-fuzzy classifier by Bayram

there are three classifiers and one feature selection method based on neuro-fuzy. (feature selection, modeling, system identification)

[fismat,feature,outputs,recog_tr,recog_te,labels,performanc...

[fismat,outputs,recog_tr,recog_te,labels,performance]=scg_n...

[fismat,outputs,recog_tr,recog_te,labels,performance]=scg_n...

Toolbox Alpert Transform by Gabriel Peyre

The Alpert transform is a multiwavelets transform based on orthogonal polynomials. (alpert, wavelets, multiwavelets)

Toolbox Alpert Transform - A toolbox to perform the Fast Mu...

array_get_val( x, ind )

array_set_val( x, ind, v )

Patch color selector by Yi Cao

Selecting colors for a number of patches to avoid neighboring patches with the same color. (color patches, data exploration)

pcsel( centers, ncolor )

k_means cluster by lulu ?

use k_means to cluster a mount of data (cluster)

y=kmeans(data,k)

KMeans Segmentation - MEX by Ahmad

Given N data elements of R dimensions (N x R matrix), it segregates the n elements into k clusters (kmeans, segmentation, clustering)

kmeansK( data_vecs, k )

classification k-means by Edgar Bernal-Flores

matrix where the values of each position is the distance of one class to another class. (kmeans)

crit_kmeans_unifor(k,datos)

k-means algorithm by Tyler London

Runs the k-means algorithm on N random points on a given shape. (kmeans, signal processing, can anyone help me ou...)

kMeans(numPoints, numClusters, shape, drawOn, showOn)

Histogram Binwidth Optimization by Hideaki Shimazaki

Function `sshist' returns optimal number of bins in a histogram used for density estimation. (binwidth, histogram, optimization)

sshist(x,N)

Fuzzy c-means segmentation by Santle Camilus

This program segments an image into 2 partitions using standard Fuzzy k-means algorithm. (clustering, cmeans, image segmentation)

fuzzycmeans.m

CVAP: Cluster Validity Analysis Platform (cluster analysis and validation tool) by Kaijun Wang

supplying over 17 validity indices and 5 clustering algorithms based on GUI (cluster validation, clustering analysis, statistics)

[dout,wide,dmin]=data_normalization(data,choise,oldwide,old...

[idx,netsim,dpsim,expref,pref,lowp,highp]=apclusterK(...

[idx,netsim,dpsim,expref]=apcluster(s,p,varargin);

Image Acquisition and Processing with MATLAB® Webinar Files by Alan Hwang

This file contains the demos used in the Image Acquisition and Processing with MATLAB® Webinar. (blister, image acquisition, webinar)

BlisterRead(RGB)

Blister_GUI(varargin)

BlisterPackInspection.m

BioMedical EDU Webinar - Statistics and Curve Fitting by Peter Perkins

Code and data used during the BioMedical EDU Webinar given on 10/8/03. (biomedical, data, webinar)

myfit(hours,sulfate)

allCode.m

plotClusts.m

Hill-Climbing Color Image Segmentation by YIQUN

color image segmentation using hill-climbing algorithm and kmeans in CIE Lab. (hillclimbing, kmeans, image processing)

HillClimbingSegment(sImgPath,iBinNum)

RGB2Lab(R,G,B)

Efficient K-Means Clustering using JIT by Yi Cao

A simple but fast tool for K-means clustering (clustering, jit, kmeans)

[gIdx,c]=k_means(X,k)

KNMCluster by Timothy Felty

Calculates means and associated clusters from input data. (audio processing, video processing, k)

[means,c]=KNMCluster(k,indata)% Inputs

K-means algorithm demo by Mauricio Martinez-Garcia

A simple implementation of the kmeans algorithm (dsp, kmeans vector quantiz...)

simple_kmeans(X,K,maxerr)

km_demo.m

k-Means Projective Clustering by Yohai Devir

Perform projective clusterig (statistics, clustering, kmeans)

kMeansProjClustering(pointsCoords, k, options)

setDefaultValues(myStruct,varargin)

Statistical Learning Toolbox by Dahua Lin

Functions for statistical learning, pattern recognition and computer vision, covering many topics. (classification, statistical learning, pattern recognition)

annsearch(X0, X, k, varargin)

edl_batchexp(expfun, scrpath, env, logger, filter, runopt)

edl_buildiidxdict(S, idxfn)

Fast Circular Cross Covariance by Ehsan Azar

Fast Circular Cross Covariance of two signals (filter design, filter analysis, fast circular cross c...)

[lags,cc]=CXCOV(a,b)

Surface Curvature by Daniel Claxton

Vectorized surface curvature computation (curvature, gaussian, mean curvature)

surfature(X,Y,Z),