subject areacomputer sciencemore specific subject areaimage processing , character recognitiontype of dataimagehow data was acquiredhand writing and scannerdata formatjpg imageexperimental factorswe ask 30 students to write in each cell of a table all tifinagh characters , we use an epson 10000xl to data scan , and we add 13 more features to take on consideration horizontal and vertical inclinationexperimental features1376 image with a size of 3030px ( 43 images therefore , the integration of the tifinagh alphabet in new information technologies and communication ( ict ) and engage in research in this field has become a major necessity .the amazigh language is spoken by about 30 million people in north africa ( the oasis of siwa in egypt , morocco through libya , tunisia , algeria , niger , mali , burkina faso and mauritania ) .due to the diversity of hand writing characters , there are two big approaches in this field and both need a dataset to be executed : the first one is based on complex classifiers like artificial neural network or support vector machine ; those classifiers need a dataset to be trained to classify characters . the other approaches also need a dataset this time to find a normalization of each character.the data set is very useful to train classification system for tifinagh hand writing , that remain an active area of research.the dataset is the first free and on line dataset for handwriting tifinagh character without formalities . the amazigh language is considered as official language only in 2003 . therefore , the integration of the tifinagh alphabet in new information technologies and communication ( ict ) and engage in research in this field has become a major necessity . the amazigh language is spoken by about 30 million people in north africa ( the oasis of siwa in egypt , morocco through libya , tunisia , algeria , niger , mali , burkina faso and mauritania ) . due to the diversity of hand writing characters , there are two big approaches in this field and both need a dataset to be executed : the first one is based on complex classifiers like artificial neural network or support vector machine ; those classifiers need a dataset to be trained to classify characters . the other approaches also need a dataset this time to find a normalization of each character . the data set is very useful to train classification system for tifinagh hand writing , that remain an active area of research . the dataset is the first free and on line dataset for handwriting tifinagh character without formalities . we ask 30 people ( 17 male and 13 female ) to write the 32 tifinagh ( fig . 1 ) characters on one page , and we add 13 more features to take on consideration horizontal and vertical inclination . the extraction steps were:we use the horizontal histogram to correct the inclination of every page .using connected components algorithm we detect the center of each character .we extract 31 sub - images of 3030px that contain the characters ( fig . 2).the sub - image are named using latin character mentioned in fig . 1 for each character followed by number from 1 to 30 ( a1,a2  a43 ) . for character with sub point we use a double character ( hh or zz ) . for epsilon we use the horizontal histogram to correct the inclination of every page . using connected components the sub - image are named using latin character mentioned in fig . 1 for each character followed by number from 1 to 30 ( a1,a2  a43 ) . for character with sub point we use a double character ( hh or zz ) . for epsilon aa43 ) . to automatically explore the dataset or to extract features from the whole dataset we propose the following matlab code : data_setfilefolder = fullfile(data_set);diroutput = dir(fullfile(filefolder,.jpg))filenames = { diroutput.name}numframes = numel(filenames)cd  data_setp = imread(filenames{2});//we read and converts to gray level the first image then we call the //feature extraction processd = imread(p);d = double(d)/255;y = rgb2gray(d);t = zmoment(y,11 ) ; // call the feature extractionb = t ; //we add the t to the data matrix// we repeat the same treatment for the rest of the data setfor i=2:1240p = m{i};d = imread(p);d = double(d)/255;y = rgb2gray(d);t = zmoment(y,11 ) ; // call the feature extraction function(zernike for //
the tifinagh alphabet - ircam is the official alphabet of the amazigh language widely used in north africa [ 1 ] . 
 it includes thirty - one basic letter and two letters each composed of a base letter followed by the sign of labialization . 
 normalized only in 2003 ( unicode ) [ 2 ] , icram - tifinagh is a young character repertoire . which needs more work on all levels . 
 in this context we propose a data set for handwritten tifinagh characters composed of 1376 image ; 43 image for each character . 
 the dataset can be used to train a tifinagh character recognition system , or to extract the meaning characteristics of each character .