% RIDGESEGMENT - Normalises fingerprint image and segments ridge region%% Function identifies ridge regions of a fingerprint image and returns a% mask identifying this region.  It also normalises the intesity values of% the image so that the ridge regions have zero mean, unit standard% deviation.%% This function breaks the image up into blocks of size blksze x blksze and% evaluates the standard deviation in each region.  If the standard% deviation is above the threshold it is deemed part of the fingerprint.% Note that the image is normalised to have zero mean, unit standard% deviation prior to performing this process so that the threshold you% specify is relative to a unit standard deviation.%% Usage:   [normim, mask, maskind] = ridgesegment(im, blksze, thresh)%% Arguments:   im     - Fingerprint image to be segmented.%              blksze - Block size over which the the standard%                       deviation is determined (try a value of 16).%              thresh - Threshold of standard deviation to decide if a%                       block is a ridge region (Try a value 0.1 - 0.2)%% Returns:     normim - Image where the ridge regions are renormalised to%                       have zero mean, unit standard deviation.%              mask   - Mask indicating ridge-like regions of the image, %                       0 for non ridge regions, 1 for ridge regions.%              maskind - Vector of indices of locations within the mask. %% Suggested values for a 500dpi fingerprint image:%%   [normim, mask, maskind] = ridgesegment(im, 16, 0.1)%% See also: RIDGEORIENT, RIDGEFREQ, RIDGEFILTER% Peter Kovesi         % School of Computer Science & Software Engineering% The University of Western Australia% pk at csse uwa edu au% http://www.csse.uwa.edu.au/~pk%% January 2005function [normim, mask, maskind] = ridgesegment(im, blksze, thresh)        im = normalise(im,0,1);  % normalise to have zero mean, unit std dev        fun = inline('std(x(:))*ones(size(x))');        stddevim = blkproc(im, [blksze blksze], fun);        mask = stddevim > thresh;    maskind = find(mask);        % Renormalise image so that the *ridge regions* have zero mean, unit    % standard deviation.    im = im - mean(im(maskind));    normim = im/std(im(maskind));