index_db.m

基于小波变换的特征检索算法

function [fe, fs] = index_db(namefile, imagedir, nlevels, filt, edge)
% INDEX_DB Wavelet-based feature extraction from database
%
% Input:
%	namefile: the file contains the names of all images in database
%	imagedir: the directory where all images are
%	nlevels: (optional) number of wavelet pyramid levels (default 3)
%	filt:	(optional) string naming a standard filter 
%		(see wfilters, default 'haar')
%	edge:	(optional) specifies edge-handling 
%		(see dwtmode, default 'per')
%
% Output: (one column per image)	
%	fe:	feature vectors based on mean energies
%		of the wavelet coefficients
%	fs: 	feature vectors based on generalized Gaussian pdf parameters
%		(Maximum Likelihood Estimation)
%
% Note:
%	To write the features into file that read from PC (little-endian
%	format) then use:
%
%		fid = fopen(indexfile, 'wb', 'ieee-le');
%		fwrite(fid, fe, 'float');
%
% See also: WAVEFEAT, WAVEFEAT_ALL

% Checking inputs
if exist(namefile, 'file') == 0
    error('Can not find namefile.');
end

if exist(imagedir, 'dir') == 0
    error('Can not find imagedir.');
end

if exist('nlevels', 'var') == 0
    nlevels = 3;
end

if exist('filt', 'var') == 0
    filt = 'db4';
end

if exist('edge', 'var') == 0
    edge = 'per';
end

% Filters from name
[LoF_D, HiF_D] = wfilters(filt, 'd');

% Set edge-handling mode
% dwtmode(edge);
st = dwtmode('status', 'nodisp');
if ~strcmp(st, edge)
    dwtmode(edge);
end

% Initialize
fm = [];
fs = [];
cd(imagedir);
name_fid = fopen(namefile, 'rt');

% Main process
while 1
    % Each image is in one line
    line = fgetl(name_fid);
    if ~isstr(line)
	break;
    end
    
    % Image name is the first string
    file = sscanf(line, '%s', 1);%Read string under format control %sfrom line , 1 data is read,
    
    if exist(file, 'file') == 0
	error('Bad: Image file not found.');
    end

    % Compute features
    [fv1, fv2, fv3, w] = wavefeat(file, nlevels, LoF_D, HiF_D);
    
    fm = [fm, fv1];
    fs = [fs, fv3];   
end

fclose(name_fid);