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LBP.cpp
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/**
* LBP.cpp
* Implements the local binary pattern (LBP) texture descriptors
*
* Created on: Jan 25, 2013
* Author: Navid Nourani-Vatani
* Email: [email protected]
*
* The methods implemented here are inspired by the Matlab code available
* from web site of the University of Oulu:
* http://www.cse.oulu.fi/CMV/Downloads/LBPMatlab
* You should cite the appropriate publications when using this code.
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
*/
#include "LBP.hpp"
using namespace lbp;
/**
* Constructors
*/
LBP::LBP( void )
: type( LBP_MAPPING_NONE ), samples( 0 ), num( 0 ), fftIn( NULL ), fftOut( NULL ), fftPlan( NULL ),
fftN( 0 ), fftHermN( 0 ) {
}
LBP::LBP( unsigned int _samples, MappingType _type )
: type( _type ), samples( _samples ), num( 0 ), fftIn( NULL ), fftOut( NULL ),
fftPlan( NULL ), fftN( 0 ), fftHermN( 0 ) {
generateMapping();
if( type == LBP_MAPPING_HF ) {
initHF();
}
}
LBP::~LBP() {
if( fftIn != NULL ) {
fftw_destroy_plan( fftPlan );
fftw_free( fftIn );
delete[] fftOut;
}
}
int* LBP::get_bits(int n, int bitswanted){
int *bits = (int*)malloc(sizeof(int) * bitswanted);
int k;
for(k=0; k<bitswanted; k++){
int mask = 1 << k;
int masked_n = n & mask;
int thebit = masked_n >> k;
bits[k] = thebit;
}
return bits;
}
unsigned int LBP::fromBin(vector<int> &bin, int len)
{
// double check the binary string is of valid length
if (bin.size() != len ) {
cout << "ERROR: The binary string length does not match." << endl;
exit(1);
}
unsigned int dec = 0;
for (int i = 0; i < len; ++i) {
dec += bin.at(i) * pow(2., i);
}
return dec;
}
/** ******************************************************************
*
* Mapping part
*
*/
LBP & LBP::generateMapping() {
return generateMapping( this->samples, this->type );
}
LBP & LBP::generateMapping( unsigned int samples, MappingType type ) {
this->orbits.clear();
this->table.clear();
this->rtable.clear();
this->rbin.clear();
this->uninum.clear();
this->num = 0;
this->type = type;
this->samples = samples;
int newMax = 0; //number of patterns in the resulting LBP code
int index = 0;
if( type == LBP_MAPPING_NONE ) {
newMax = (int) pow( 2., (int) samples );
for( unsigned int i = 0; i < newMax; i++ ) {
table.push_back(i);
}
}
else if ( type == LBP_MAPPING_U2ROB ){
// Robust Uniform 2
newMax = samples * (samples - 1) + 3;
for (unsigned int i = 0; i < pow(2., (int) (samples) ); i++) {
unsigned int j = rotateLeft(i, samples);
int numt = NumberOfSetBits(i ^ j);
if (numt <= 2) {
table.push_back(index);
index = index + 1;
}
else{
// only consider the non-uniform patterns
int* bts = get_bits(i, samples);
vector<int> bts_cp(samples);
std::copy(bts, bts + samples, bts_cp.begin());
bool found1 = false;
unsigned int binVal1 = -1;
int unicnt = 0; // number of uniform patterns converted from bts
list<int> rmap; // robust mapping for non-uniform pattern
// case 1: (010)-->(000)
for (int p = 0; p <= (samples - 3); ++p) {
int b1 = bts[p];
int b2 = bts[p+1];
int b3 = bts[p+2];
if (i == 42) {
printf("%d-%d-%d\n", b1, b2, b3);
}
if ( b1 == 0 && b2 == 1 && b3 == 0)
{
bts_cp[p+1] = 0;
found1 = true;
}
}
// find out what's the new histogram value
if (found1) {
binVal1 = fromBin(bts_cp, samples);
rmap.push_back(binVal1);
// now check if the new value is uniform pattern or not
unsigned int n = rotateLeft(binVal1, samples);
int nt = NumberOfSetBits(binVal1 ^ n);
if(nt <= 2){
unicnt++;
}
}
// case 2: (101)-->(111)
// reset for the second case
std::copy(bts, bts + samples, bts_cp.begin());
bool found2 = false;
unsigned int binVal2 = -1;
for (int p = 0; p <= samples - 3; ++p) {
int b1 = bts[p];
int b2 = bts[p+1];
int b3 = bts[p+2];
if (i == 42) {
printf("%d-%d-%d\n", b1, b2, b3);
}
if ( b1 == 1 && b2 == 0 && b3 == 1)
{
bts_cp[p+1] = 1;
found2 = true;
if (i == 13) {
for (int z = 0; z < bts_cp.size(); ++z) {
cout << bts_cp[z];
}
cout << endl;
}
}
}
// find out what's the new histogram value
if (found2) {
binVal2 = fromBin(bts_cp, samples);
rmap.push_back(binVal2);
// now check if the new value is uniform pattern or not
unsigned int n = rotateLeft(binVal2, samples);
int nt = NumberOfSetBits(binVal2 ^ n);
if(nt <= 2){
unicnt++;
}
}
// this non-uniform string can map to one/some uniform pattern(s) and non-uniform pattern(s)
if (found1 || found2) {
if (i >= 240 || i == 42) {
printf("%d -->%d or %d with %d, %d \n", i, binVal1, binVal2, index, unicnt);
}
// after mapping, we only interested in the new bin index
rbin.push_back(index);
uninum.push_back(unicnt);
rtable.push_back(rmap);
// we still want to count for this bin,
// so that afterwards to disperse the occurance to other converting patters
table.push_back(index);
index = index + 1;
}else
// no 'robust pattern' found, stick to original plan
table.push_back( 255 );
free(bts);
}
}
}
else if( type == LBP_MAPPING_U2 ) {
// Uniform 2
newMax = samples * (samples - 1) + 3;
for( unsigned int i = 0; i < pow( 2., (int) (samples) ); i++ ) {
// Rotate left
// unsigned int bg = ((i & (1 << (samples - 1))) >> (samples - 1)); // bitget(i,samples)
// unsigned int bs = (i << 1) & ((int) pow( 2., (int) samples ) - 1); // bitshift( i, 1, samples )
// unsigned int j = (bs + bg) & ((int) pow( 2., (int) samples ) - 1); // bitset( bs, 1, bg )
unsigned int j = rotateLeft( i, samples );
int numt = NumberOfSetBits( i ^ j ); // sum(bitget(bitxor(i,j),1:samples));
//number of 1->0 and 0->1 transitions
//in binary string
//x is equal to the
//number of 1-bits in
//XOR(x,Rotate left(x))
if( numt <= 2 ) {
table.push_back( index );
index = index + 1;
}
else {
table.push_back( newMax - 1 );
}
}
}
else if( type == LBP_MAPPING_RI ) {
long N = (int) pow( 2., (int) samples );
// Rotation Invariant
int * tmpMap = new int[N];
memset( (void *)tmpMap, -1, N );
for( unsigned long i = 0; i < N; i++ ) {
tmpMap[i] = -1;
unsigned long rm = i;
unsigned long r = i;
for( int j = 1; j <= samples - 1; j++ ) {
r = rotateLeft( r, samples );
if( r < rm )
rm = r;
}
if( tmpMap[rm] < 0 ) {
tmpMap[rm] = newMax;
newMax = newMax + 1;
}
table.push_back( tmpMap[rm] );
}
}
else if( type == LBP_MAPPING_RIU2 ) {
// Rotation invariant uniform 2
newMax = samples + 2;
for( unsigned int i = 0; i <= pow( 2., (int) samples ) - 1; i++ ) {
unsigned int j = rotateLeft( i, samples ); //bitset( bitshift( i, 1, samples ), 1, bitget( i, samples ) ); // rotate left
unsigned int numt = NumberOfSetBits( i ^ j ); //sum(bitget(bitxor(i,j),1:samples));
if( numt <= 2 )
table.push_back( NumberOfSetBits( i ) );
else
table.push_back( samples + 1 );
}
}
else if( type == LBP_MAPPING_HF ) {
// Histogram Fourier
newMax = samples * (samples - 1) + 3;
table.push_back( newMax - 3 );
for( unsigned int i = 1; i <= pow( 2., (int) samples ) - 2; i++ ) {
unsigned int j = rotateLeft( i, samples ); // bitset(bitshift(i,1,samples),1,bitget(i,samples)); %rotate left
unsigned int numt = NumberOfSetBits( i ^ j ); // sum(bitget(bitxor(i,j),1:samples)); %number of 1->0 and 0->1 transitions
if( numt == 2 ) { // Uniform pattern
unsigned int n = NumberOfSetBits( i ); // sum(bitget(i,1:samples)); %Number of 1-bits
unsigned int bc = j ^ ((unsigned int) pow( 2., (int) samples ) - 1);
unsigned int ba = bc & i;
unsigned int f = trailingZeroInd( ba ) + 1; //find(bitget(bitand(i,bitcmp(j,samples)),1:samples)); // Rotation index of the bit pattern
unsigned int r = ((int) floor( n / 2. ) + f) % samples;
index = (n - 1) * samples + r;
table.push_back( index );
}
else { // Non-uniform
table.push_back( newMax - 1 );
}
}
table.push_back( newMax - 2 );
vector<int> o;
for( int i = 1; i <= samples - 1; i++ ) {
o.clear();
for( int j = ((i - 1) * samples); j <= (i * samples - 1); j++ ) {
o.push_back( j );
}
orbits.push_back( o );
}
o.clear();
o.push_back( newMax - 3 );
orbits.push_back( o );
o[0] = newMax - 2;
orbits.push_back( o );
o[0] = newMax - 1;
orbits.push_back( o );
}
else {
cerr << "Unknown mapping!" << endl;
exit(1);
}
if (type == LBP_MAPPING_U2ROB) {
this->num = 256;
}else
this->num = newMax;
return *this;
}
/**
*
*/
bool LBP::saveMapping( string fileName ) {
ofstream ofs( fileName.c_str(), ios::out );
if( ! ofs ) {
cerr << "File \'" << fileName << "\' could not be opened" << endl;
return false;
}
ofs << "LBPMapping" << endl;
ofs << "version " << 1 << endl;
ofs << "type " << MappingTypeStr[ type ] << endl;
ofs << "samples " << samples << endl;
ofs << "maxnum " << num << endl;
ofs << "table ";
for( int i = 0; i < table.size(); i++ ) {
ofs << table[i] << " ";
}
ofs << endl;
if( type == LBP_MAPPING_HF ) {
ofs << "orbits ";
for( int i = 0; i < orbits.size(); i++ ) {
for(int j = 0; j < (orbits[i]).size(); j++ ) {
ofs << orbits[i][j] << " ";
}
ofs << "-1 ";
}
ofs << endl;
}
return true;
}
bool LBP::loadMapping( string fileName ) {
ifstream ifs( fileName.c_str(), ios::in );
if( ! ifs ) {
cerr << "File \'" << fileName << "\' could not be opened" << endl;
return false;
}
string s; int i;
// Get file type
ifs >> s;
if( s.compare("LBPMapping") ) {
cerr << fileName << " is not a LBPMapping file." << endl;
return false;
}
// Get verion
ifs >> s >> i;
// Get mapping type
ifs >> s >> s;
this->type = strToType(s);
// Get samples
ifs >> s >> this->samples;
// Get maxnum
ifs >> s >> this->num;
// Get table
ifs >> s;
this->table.clear();
for (int j = 0; j < pow(2., (double)samples); j++ ) {
ifs >> i;
table.push_back( i );
}
if ( type != LBP_MAPPING_HF ) {
return true;
}
// Get orbits for HF
this->orbits.clear();
ifs >> s;
vector<int> o;
while( ifs >> i ) {
if( i < 0 ) { // -1 are used as separators
orbits.push_back(o);
o.clear();
continue;
}
o.push_back(i);
}
return true;
}
/** ******************************************************************
*
* Descriptor part
*
*/
LBP & LBP::calcLBP( Mat d_img, double radius, bool borderCopy ) {
// clock_t startTime, endTime, sT, eT;
// vector<double> times;
// double minVal, maxVal;
// namedWindow( "lbp", 0 );
// Mat dummy( 300, 260, CV_8UC1);
// Make sure the image has Double precision version
if( d_img.type() < CV_64F ) {
d_img.convertTo( d_img, CV_64F );
}
// Make a copy of the image border the same size as the radius
if( borderCopy ) {
Mat tmp( d_img.rows+2*radius, d_img.cols+2*radius, CV_64F );
copyMakeBorder( d_img, tmp, radius, radius, radius, radius, BORDER_WRAP, Scalar(0) );
d_img = tmp.clone();
}
double spoints[samples][2];
double a = 2 * M_PI / samples;
double miny = +INT_MAX;
double maxy = -INT_MAX;
double minx = +INT_MAX;
double maxx = -INT_MAX;
for( int i = 0; i < samples; i++ ) {
spoints[i][0] = +radius * cos( double( i * a ) );
spoints[i][1] = -radius * sin( double( i * a ) );
minx = (spoints[i][0] < minx ? spoints[i][0] : minx);
maxx = (spoints[i][0] > maxx ? spoints[i][0] : maxx);
miny = (spoints[i][1] < miny ? spoints[i][1] : miny);
maxy = (spoints[i][1] > maxy ? spoints[i][1] : maxy);
}
// Determine the dimensions of the input image.
int xsize = d_img.cols;
int ysize = d_img.rows;
// Block size, each LBP code is computed within a block of size bsizey*bsizex
int bsizex = ceil( max( maxx, 0. ) ) - floor( min( minx, 0. ) ) + 1;
int bsizey = ceil( max( maxy, 0. ) ) - floor( min( miny, 0. ) ) + 1;
// Minimum allowed size for the input image depends
// on the radius of the used LBP operator.
if( xsize < bsizex || ysize < bsizey ) {
cerr << "Too small input image. Should be at least (2*radius+1) x (2*radius+1)" << endl;
return *this;
}
// Coordinates of origin (0,0) in the block
int origx = 1 - floor( min( minx, 0. ) ) - 1;
int origy = 1 - floor( min( miny, 0. ) ) - 1;
// Calculate dx and dy;
int dx = xsize - bsizex + 1;
int dy = ysize - bsizey + 1;
// Fill the center pixel matrix C.
// d_C is a shallow copie. But that's OK because we are not changing the values
// but only comparing to N
Mat d_C( d_img, Rect( origx, origy, dx, dy ) );
// Initialize the result matrix with zeros.
Mat result( dy, dx, CV_64FC1);
result = Mat::zeros( dy, dx, CV_64FC1 );
Mat D( dy, dx, CV_64FC1);
Mat N( dy, dx, CV_64FC1);
// Compute the LBP code image
// startTime = clock();
for( int i = 0; i < samples; i++ ) {
double x = spoints[i][0] + origx;
double y = spoints[i][1] + origy;
// Calculate floors, ceils and rounds for the x and y.
int fy = floor( y );
int cy = ceil( y );
int ry = round( y );
int fx = floor( x );
int cx = ceil( x );
int rx = round( x );
// Check if interpolation is needed.
if( (fabs( x - rx ) < 1e-6) && (fabs( y - ry ) < 1e-6) ) {
// Interpolation is not needed, use original data types
// N is a shallow copy. But that's OK because we are not changing the value
// but only comparing to C
Mat N( d_img, Rect( rx, ry, dx, dy ) );
compare( N, d_C, D, CMP_GE ); // D = (N >= C);
}
else {
// Interpolation needed, use double type images
double tx = x - fx;
double ty = y - fy;
// Calculate the interpolation weights.
double w1 = (1 - tx) * (1 - ty);
double w2 = tx * (1 - ty);
double w3 = (1 - tx) * ty;
double w4 = tx * ty;
// Compute interpolated pixel values
// N = w1 * d_img( Rect( fx, fy, dx, dy ) ) + w2 * d_img( Rect( cx, fy, dx, dy ) )
// + w3 * d_img( Rect( fx, cy, dx, dy ) )
// + w4 * d_img( Rect( cx, cy, dx, dy ) );
// The below operations are about 20% faster than the above
addWeighted( d_img( Rect( fx, fy, dx, dy ) ), w1,
d_img( Rect( cx, fy, dx, dy ) ), w2, 0, N );
addWeighted( d_img( Rect( fx, cy, dx, dy ) ), w3, N, 1, 0, N );
addWeighted( d_img( Rect( cx, cy, dx, dy ) ), w4, N, 1, 0, N );
compare( N, d_C, D, CMP_GE ); // D = (N >= C);
}
// Update the result matrix.
double v = pow( 2., i ) / 255.; // Divide by 255 because D is 0/255 rather than 0/1
D.convertTo( D, CV_64F );
result = result + (v * D);
}
result.convertTo( result, CV_8U );
// endTime = clock();
// times.push_back( (endTime - startTime) );
// cout << "lbp calc took " << times.back() << " cycles" << endl;
// startTime = clock();
// Apply mapping if it is defined
if( type != LBP_MAPPING_NONE ) {
MatIterator_<unsigned char> it = result.begin<unsigned char>(), it_end = result.end<
unsigned char>();
for( ; it != it_end; ++it ) {
*it = table[(*it)];
}
}
// endTime = clock();
// times.push_back( (endTime - startTime) );
// cout << "mapping took " << times.back() << " cycles" << endl;
// Store the final result
lbpImage = result.clone();
#if 0
for( int j = 0; j < lbpImage.rows; j++ ) {
for( int i = 0; i < lbpImage.cols; i++ ) {
//cout.width(3);
cout << int(lbpImage.at<unsigned char>(j,i)) << " ";
}
cout << endl;
}
#endif
return *this;
}
bool LBP::saveLBPImage( string fileName ) {
return cv::imwrite( fileName, this->lbpImage );
}
/** ******************************************************************
*
* Histogram part
*
*/
LBP & LBP::calcHist( void ) {
return calcHist( &lbpImage );
}
LBP & LBP::calcHist( Mat mask ) {
return calcHist( &lbpImage, &mask );
}
LBP & LBP::calcHist( Mat * lbpImg, Mat * mask ) {
if( lbpImg == NULL ) {
lbpImg = &(this->lbpImage);
}
int histSize = num;
float range[] = { 0, num };
const float* histRange = { range };
if( mask == NULL ) {
cv::calcHist( lbpImg, 1, 0, Mat(), // do not use mask
hist, 1, &histSize, &histRange, true, // the histogram is uniform
false // do not accumulate
);
}
else {
cv::calcHist( lbpImg, 1, 0, *mask, // use mask
hist, 1, &histSize, &histRange, true, // the histogram is uniform
false // do not accumulate
);
}
// now we need sort out for RLBP case
// by re-allocate bin element for robust patterns
if (type == LBP_MAPPING_U2ROB ) {
for (int i = 0; i < rbin.size(); ++i) {
int bin = rbin.at(i);
int unicnt = uninum.at(i);
list<int> rmap = rtable.at(i);
float binVal = hist.at<float>(bin);
printf("%d : %d - %.2f, rpattern: %d, unicnt:%d \n", i, bin, binVal, rmap.size(), unicnt);
// if none of converted pattern is uniform, then accumulate it to non-uniform patterns
if (unicnt == 0 ) {
// cout << "still non-uni: " << i << ", binVal: " << binVal << endl;
hist.at<float>(255) += binVal;
hist.at<float>(bin) = 0;
}
// if all converted patterns are uniform, that's easy too
if (unicnt == rmap.size()) {
float newVal = binVal / unicnt;
list<int>::iterator it;
for ( it = rmap.begin(); it != rmap.end(); ++it) {
hist.at<float>( *it ) += newVal;
}
hist.at<float>(bin) = 0;
}
if (unicnt > 0 && rmap.size() > unicnt) {
cout << "partially non-uni: " << i << ", binVal: " << binVal << endl;
float newVal = binVal / rmap.size();
hist.at<float>(255) += newVal;
hist.at<float>(rmap.front()) += newVal;
hist.at<float>(bin) = 0;
}
}
printf("%d - %d - %d\n", rbin.size(), rtable.size(), uninum.size());
}
return *this;
}
vector<double> LBP::getHist( bool norm ) {
cout << " *** bin number:" << num << ", hist size: " << hist.rows << endl;
vector<double> h( hist.rows );
Scalar sum( 1 );
// normalization value
if( norm || type == LBP_MAPPING_HF ) {
sum = cv::sum( hist );
}
for( int i = 0; i < hist.rows; i++ ) {
h[i] = hist.at<float>( i ) / sum[0];
}
if( type == LBP_MAPPING_HF ) {
h = constructHF( h );
}
return h;
}
void LBP::initHF( void ) {
// All the vectors in the orbit have at least the same size as the first one.
// only the last 3 are off size 1 which are not converted anyway
fftN = this->orbits[0].size();
// Since the input data are real we take advantage of Hermetian redundancy. This
// gives us a speed up
fftHermN = floor( fftN / 2 ) + 1;
// If the size of this fft array is different from previous
if( fftN != fftN && fftIn != NULL ) {
fftw_free( fftIn );
delete[] fftOut;
fftIn = NULL;
fftOut = NULL;
}
// If the in/out arrays are uninitialized
if( fftIn == NULL ) {
fftIn = (double *) fftw_malloc( sizeof(double) * fftN );
fftOut = new complex<double> [fftHermN];
}
// Setup the fft plan
fftPlan = fftw_plan_dft_r2c_1d(
fftN, fftIn, reinterpret_cast<fftw_complex *>( fftOut ), FFTW_ESTIMATE);
}
vector<double> LBP::constructHF( vector<double> h ) {
if( this->type != LBP_MAPPING_HF ) {
cerr << "The mapping type must be " << MappingTypeStr[LBP_MAPPING_HF] << endl;
return h;
}
initHF();
// Size of the output vector
// int FVLEN = (samples - 1) * (floor( samples / 2 ) + 1) + 3;
// hf.reserve( FVLEN );
hf.clear();
for( int j = 0; j < this->orbits.size(); j++ ) {
if( orbits[j].size() > 1 ) {
// transfer in the data
for( int i = 0; i < fftN; i++ ) {
fftIn[i] = h[orbits[j][i]];
}
fftw_execute( fftPlan );
// read out the data
for( int i = 0; i < fftHermN; i++ ) {
hf.push_back( abs( fftOut[i] ) );
}
}
else {
hf.push_back( h[orbits[j][0]] );
}
}
return hf;
}
/** ******************************************************************
*
* Others part
*
*/
std::string LBP::toString( bool verbose ) const {
string s = "LBP = \n";
s += "\t type: " + MappingTypeStr[type] + "\n";
if( verbose ) {
s += "\t table: [";
for( int i = 0; i < table.size(); i++ )
s += SSTR( table[i] ) + (i < table.size()-1 ? ", " : "");
s += "]\n";
}
else {
s += "\t table: [1x" + SSTR( pow( 2., (int) this->samples ) )+ (string) "]\n";
}
s += "\t samples: " + SSTR( this->samples )+ (string) "\n";
s += "\t num: " + SSTR( this->num )+ (string) "\n";
if( this->type == LBP_MAPPING_HF ) {
if (verbose) {
s += "\t orbits: {";
for (int i = 0; i < orbits.size(); i++ ) {
s += "{";
for (int j = 0; j < orbits[i].size(); j++) {
s += SSTR( orbits[i][j]) + (j < orbits[i].size()-1 ? ", " : "");
}
s += (string)"}" + (i < orbits.size()-1 ? ", " : "");
}
s += "}\n";
}
else {
s += "\t orbits: {" + SSTR( this->orbits.size() )+ (string) "x1}\n";
}
}
return s;
}