diff --git a/CMakeLists.txt b/CMakeLists.txt
index 0e5ed59..1decf2f 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -39,6 +39,13 @@ add_executable( example_11-02 example_11-02.cpp )
 add_executable( example_11-03 example_11-03.cpp )
 add_executable( example_12-01 example_12-01.cpp )
 add_executable( example_12-02 example_12-02.cpp )
+add_executable( example_13-01 example_13-01.cpp )
+add_executable( example_13-02 example_13-02.cpp )
+add_executable( example_13-03 example_13-03.cpp )
+add_executable( example_14-01 example_14-01.cpp )
+add_executable( example_14-02 example_14-02.cpp )
+add_executable( example_14-03 example_14-03.cpp )
+add_executable( example_14-04 example_14-04.cpp )
 add_executable( example_16-01 example_16-01.cpp )
 
 target_link_libraries( example_02-01 ${OpenCV_LIBS} )
@@ -75,8 +82,11 @@ target_link_libraries( example_11-02 ${OpenCV_LIBS} )
 target_link_libraries( example_11-03 ${OpenCV_LIBS} )
 target_link_libraries( example_12-01 ${OpenCV_LIBS} )
 target_link_libraries( example_12-02 ${OpenCV_LIBS} )
+target_link_libraries( example_13-01 ${OpenCV_LIBS} )
+target_link_libraries( example_13-02 ${OpenCV_LIBS} )
+target_link_libraries( example_13-03 ${OpenCV_LIBS} )
+target_link_libraries( example_14-01 ${OpenCV_LIBS} )
+target_link_libraries( example_14-02 ${OpenCV_LIBS} )
+target_link_libraries( example_14-03 ${OpenCV_LIBS} )
+target_link_libraries( example_14-04 ${OpenCV_LIBS} )
 target_link_libraries( example_16-01 ${OpenCV_LIBS} )
-
-
-
-
diff --git a/HandIndoorColor.jpg b/HandIndoorColor.jpg
new file mode 100644
index 0000000..32427bb
Binary files /dev/null and b/HandIndoorColor.jpg differ
diff --git a/HandOutdoorColor.jpg b/HandOutdoorColor.jpg
new file mode 100644
index 0000000..5a3c2d8
Binary files /dev/null and b/HandOutdoorColor.jpg differ
diff --git a/HandOutdoorSunColor.jpg b/HandOutdoorSunColor.jpg
new file mode 100644
index 0000000..a35f5f6
Binary files /dev/null and b/HandOutdoorSunColor.jpg differ
diff --git a/example_13-01.cpp b/example_13-01.cpp
new file mode 100644
index 0000000..d727222
--- /dev/null
+++ b/example_13-01.cpp
@@ -0,0 +1,55 @@
+// Example 13-1. Histogram computation and display
+
+#include <opencv2/opencv.hpp>
+#include <iostream>
+
+using namespace std;
+
+int main( int argc, char** argv ){
+  if(argc != 2) {
+    cout << "Computer Color Histogram\nUsage: " <<argv[0] <<" <imagename>" << endl;
+    return -1;
+  }
+
+  cv::Mat src = cv::imread( argv[1],1 );
+  if( src.empty() ) { cout << "Cannot load " << argv[1] << endl; return -1; }
+
+  // Compute the HSV image, and decompose it into separate planes.
+  //
+  cv::Mat hsv;
+  cv::cvtColor(src, hsv, cv::COLOR_BGR2HSV);
+
+  float h_ranges[] = {0, 180}; // hue is [0, 180]
+  float s_ranges[] = {0, 256};
+  const float* ranges[] = {h_ranges, s_ranges};
+  int histSize[] = {30, 32}, ch[] = {0, 1};
+
+  cv::Mat hist;
+
+  // Compute the histogram
+  //
+  cv::calcHist(&hsv, 1, ch, cv::noArray(), hist, 2, histSize, ranges, true);
+  cv::normalize(hist, hist, 0, 255, cv::NORM_MINMAX);
+
+  int scale = 10;
+  cv::Mat hist_img(histSize[0]*scale, histSize[1]*scale, CV_8UC3);
+
+  // Draw our histogram.
+  //
+  for( int h = 0; h < histSize[0]; h++ ) {
+    for( int s = 0; s < histSize[1]; s++ ){
+      float hval = hist.at<float>(h, s);
+      cv::rectangle(
+	hist_img,
+	cv::Rect(h*scale,s*scale,scale,scale),
+	cv::Scalar::all(hval),
+	-1
+      );
+    }
+  }
+
+  cv::imshow("image", src);
+  cv::imshow("H-S histogram", hist_img);
+  cv::waitKey();
+  return 0;
+}
diff --git a/example_13-02.cpp b/example_13-02.cpp
new file mode 100644
index 0000000..089ad89
--- /dev/null
+++ b/example_13-02.cpp
@@ -0,0 +1,162 @@
+// Example 13-2. Creating signatures from histograms for EMD; note that this code is the
+// source of the data in Table 13-1, in which the hand histogram is compared in different
+// lighting conditions
+
+#include <opencv2/opencv.hpp>
+#include <iostream>
+
+using namespace std;
+
+void help( char** argv ){
+  cout << "\nCall is:\n"
+  << argv[0] <<" modelImage0 testImage1 testImage2 badImage3\n\n"
+  << "for example: " << argv[0]
+  << " HandIndoorColor.jpg HandOutdoorColor.jpg "
+  << "HandOutdoorSunColor.jpg fruits.jpg\n"
+  << "\n";
+}
+
+// Compare 3 images' histograms
+int main( int argc, char** argv ) {
+  if( argc != 5 ) { help( argv ); return -1; }
+  vector<cv::Mat> src(5);
+  cv::Mat tmp;
+  int i;
+
+  tmp = cv::imread( argv[1], 1);
+  if( tmp.empty() ) {
+    cerr << "Error on reading image 1," << argv[1] << "\n" << endl;
+    help( argv );
+    return(-1);
+  }
+
+  // Parse the first image into two image halves divided halfway on y
+  //
+  cv::Size size = tmp.size();
+  int width = size.width;
+  int height = size.height;
+  int halfheight = height >> 1;
+
+  cout <<"Getting size [[" <<tmp.cols <<"] [" <<tmp.rows <<"]]\n" <<endl;
+  cout <<"Got size (w,h): (" <<size.width <<"," <<size.height <<")" <<endl;
+
+  src[0] = cv::Mat(cv::Size(width,halfheight), CV_8UC3);
+  src[1] = cv::Mat(cv::Size(width,halfheight), CV_8UC3);
+
+  // Divide the first image into top and bottom halves into src[0] and src[1]
+  //
+  cv::Mat_<cv::Vec3b>::iterator tmpit = tmp.begin<cv::Vec3b>();
+
+  // top half
+  //
+  cv::Mat_<cv::Vec3b>::iterator s0it = src[0].begin<cv::Vec3b>();
+  for(i = 0; i < width*halfheight; ++i, ++tmpit, ++s0it) *s0it = *tmpit;
+
+  // Bottom half
+  //
+  cv::Mat_<cv::Vec3b>::iterator s1it = src[1].begin<cv::Vec3b>();
+  for(i = 0; i < width*halfheight; ++i, ++tmpit, ++s1it) *s1it = *tmpit;
+
+  // Load the other three images
+  //
+  for(i = 2; i<5; ++i){
+    src[i] = cv::imread(argv[i], 1);
+    if(src[i].empty()) {
+      cerr << "Error on reading image " << i << ": " << argv[i] << "\n" << endl;
+      help( argv );
+      return(-1);
+    }
+  }
+
+  // Compute the HSV image, and decompose it into separate planes.
+  //
+  vector<cv::Mat> hsv(5), hist(5), hist_img(5);
+  int h_bins = 8;
+  int s_bins = 8;
+  int hist_size[] = { h_bins, s_bins }, ch[] = {0, 1};
+  float h_ranges[] = { 0, 180 }; // hue range is [0,180]
+  float s_ranges[] = { 0, 255 };
+  const float* ranges[] = { h_ranges, s_ranges };
+  int scale = 10;
+
+  for(i = 0; i<5; ++i) {
+    cv::cvtColor( src[i], hsv[i], cv::COLOR_BGR2HSV );
+    cv::calcHist( &hsv[i], 1, ch, cv::noArray(), hist[i], 2, hist_size, ranges, true );
+    cv::normalize( hist[i], hist[i], 0, 255, cv::NORM_MINMAX );
+    hist_img[i] = cv::Mat::zeros( hist_size[0]*scale, hist_size[1]*scale, CV_8UC3 );
+
+    // Draw our histogram For the 5 images
+    //
+    for( int h = 0; h < hist_size[0]; h++ )
+      for( int s = 0; s < hist_size[1]; s++ ) {
+	float hval = hist[i].at<float>(h, s);
+	cv::rectangle(
+	  hist_img[i],
+	  cv::Rect(h*scale, s*scale, scale, scale),
+	  cv::Scalar::all(hval),
+	  -1
+	);
+      }
+  }
+
+  // Display
+  //
+  cv::namedWindow( "Source0", 1 );cv::imshow( "Source0", src[0] );
+  cv::namedWindow( "HS Histogram0", 1 );cv::imshow( "HS Histogram0", hist_img[0] );
+
+  cv::namedWindow( "Source1", 1 );cv::imshow( "Source1", src[1] );
+  cv::namedWindow( "HS Histogram1", 1 ); cv::imshow( "HS Histogram1", hist_img[1] );
+
+  cv::namedWindow( "Source2", 1 ); cv::imshow( "Source2", src[2] );
+  cv::namedWindow( "HS Histogram2", 1 ); cv::imshow( "HS Histogram2", hist_img[2] );
+
+  cv::namedWindow( "Source3", 1 ); cv::imshow( "Source3", src[3] );
+  cv::namedWindow( "HS Histogram3", 1 ); cv::imshow( "HS Histogram3", hist_img[3] );
+
+  cv::namedWindow( "Source4", 1 ); cv::imshow( "Source4", src[4] );
+  cv::namedWindow( "HS Histogram4", 1 ); cv::imshow( "HS Histogram4", hist_img[4] );
+
+  // Compare the histogram src0 vs 1, vs 2, vs 3, vs 4
+  cout << "Comparison:\n"
+  << "Corr                Chi                Intersect                Bhat\n"<< endl;
+  
+  for(i=1; i<5; ++i) { // For each histogram
+    cout << "Hist[0] vs Hist[" << i << "]: " << endl;;
+    for(int j=0; j<4; ++j) { // For each comparison type
+      cout << "method[" << j << "]: " << cv::compareHist(hist[0],hist[i],j) << " ";
+    }
+    cout << endl;
+  }
+
+  //Do EMD and report
+  //
+  vector<cv::Mat> sig(5);
+  cout << "\nEMD: " << endl;
+
+  // Oi Vey, parse histograms to earth movers signatures
+  //
+  for( i=0; i<5; ++i) {
+
+    vector<cv::Vec3f> sigv;
+
+    // (re)normalize histogram to make the bin weights sum to 1.
+    //
+    cv::normalize(hist[i], hist[i], 1, 0, cv::NORM_L1);
+    for( int h = 0; h < h_bins; h++ )
+      for( int s = 0; s < s_bins; s++ ) {
+	float bin_val = hist[i].at<float>(h, s);
+	if( bin_val != 0 )
+	  sigv.push_back( cv::Vec3f(bin_val, (float)h, (float)s));
+      }
+
+    // make Nx3 32fC1 matrix, where N is the number of nonzero histogram bins
+    //
+    sig[i] = cv::Mat(sigv).clone().reshape(1);
+    if( i > 0 )
+      cout << "Hist[0] vs Hist[" << i << "]: "
+	   << EMD(sig[0], sig[i], cv::DIST_L2) << endl;
+  }
+
+  cv::waitKey(0);
+
+}
diff --git a/example_13-03.cpp b/example_13-03.cpp
new file mode 100644
index 0000000..d6dedf3
--- /dev/null
+++ b/example_13-03.cpp
@@ -0,0 +1,70 @@
+// Example 13-3. Template matching
+
+#include <opencv2/opencv.hpp>
+#include <iostream>
+
+using namespace std;
+
+void help( char** argv ){
+  cout << "\n"
+  <<"Example of using matchTemplate(). The call is:\n"
+  <<"\n"
+  <<argv[0] <<" template image_to_be_searched\n"
+  <<"\n"
+  <<" This routine will search using all methods:\n"
+  <<" cv::TM_SQDIFF 0\n"
+  <<" cv::TM_SQDIFF_NORMED 1\n"
+  <<" cv::TM_CCORR 2\n"
+  <<" cv::TM_CCORR_NORMED 3\n"
+  <<" cv::TM_CCOEFF 4\n"
+  <<" cv::TM_CCOEFF_NORMED 5\n"
+  <<"\n";
+}
+
+// Display the results of the matches
+//
+int main( int argc, char** argv ) {
+
+  if( argc != 3) {
+    help( argv );
+    return -1;
+  }
+
+  cv::Mat src, templ, ftmp[6];   // ftmp is what to display on
+
+  // Read in the template to be used for matching:
+  //
+  if((templ=cv::imread(argv[1], 1)).empty()) {
+    cout << "Error on reading template " << argv[1] << endl;
+    help( argv );return -1;
+  }
+
+  // Read in the source image to be searched:
+  //
+  if((src=cv::imread(argv[2], 1)).empty()) {
+    cout << "Error on reading src image " << argv[2] << endl;
+    help( argv );return -1;
+  }
+
+  // Do the matching of the template with the image
+  for(int i=0; i<6; ++i){
+    cv::matchTemplate( src, templ, ftmp[i], i);
+    cv::normalize(ftmp[i],ftmp[i],1,0,cv::NORM_MINMAX);
+  }
+
+  // Display
+  //
+  cv::imshow( "Template", templ );
+  cv::imshow( "Image", src );
+  cv::imshow("SQDIFF", ftmp[0] );
+  cv::imshow("SQDIFF_NORMED", ftmp[1] );
+  cv::imshow("CCORR", ftmp[2] );
+  cv::imshow("CCORR_NORMED", ftmp[3] );
+  cv::imshow("CCOEFF", ftmp[4] );
+  cv::imshow("CCOEFF_NORMED", ftmp[5] );
+
+  // Let user view results:
+  //
+  cv::waitKey(0);
+}
+
diff --git a/example_14-01.cpp b/example_14-01.cpp
new file mode 100644
index 0000000..08dffca
--- /dev/null
+++ b/example_14-01.cpp
@@ -0,0 +1,49 @@
+// Example 14-1. Finding contours based on a trackbar’s location; the contours are
+// updated whenever the trackbar is moved
+
+#include <opencv2/opencv.hpp>
+#include <iostream>
+
+using namespace std;
+
+cv::Mat g_gray, g_binary;
+int g_thresh = 100;
+
+void on_trackbar( int, void* ) {
+  cv::threshold( g_gray, g_binary, g_thresh, 255, cv::THRESH_BINARY );
+  vector< vector< cv::Point> > contours;
+  cv::findContours(
+    g_binary,
+    contours,
+    cv::noArray(),
+    cv::RETR_LIST,
+    cv::CHAIN_APPROX_SIMPLE
+  );
+  g_binary = cv::Scalar::all(0);
+
+  cv::drawContours( g_binary, contours, -1, cv::Scalar::all(255));
+  cv::imshow( "Contours", g_binary );
+
+}
+
+int main( int argc, char** argv ) {
+  if( argc != 2 || ( g_gray = cv::imread(argv[1], 0)).empty() ) {
+    cout << "Find threshold dependent contours\nUsage: " <<argv[0]
+         <<"fruits.jpg" << endl;
+    return -1;
+  }
+  cv::namedWindow( "Contours", 1 );
+
+  cv::createTrackbar(
+    "Threshold",
+    "Contours",
+    &g_thresh,
+    255,
+    on_trackbar
+  );
+  on_trackbar(0, 0);
+
+  cv::waitKey();
+
+  return 0;
+}
diff --git a/example_14-02.cpp b/example_14-02.cpp
new file mode 100644
index 0000000..7d1454d
--- /dev/null
+++ b/example_14-02.cpp
@@ -0,0 +1,70 @@
+// Example 14-2. Finding and drawing contours on an input image
+
+#include <opencv2/opencv.hpp>
+#include <algorithm>
+#include <iostream>
+
+using namespace std;
+
+struct AreaCmp {
+  AreaCmp(const vector<float>& _areas) : areas(&_areas) {}
+  bool operator()(int a, int b) const { return (*areas)[a] > (*areas)[b]; }
+  const vector<float>* areas;
+};
+
+int main(int argc, char* argv[]) {
+
+  cv::Mat img, img_edge, img_color;
+
+  // load image or show help if no image was provided
+  //
+  if( argc != 2 || (img = cv::imread(argv[1],cv::IMREAD_GRAYSCALE)).empty() ) {
+    cout << "\nExample 14_2 Drawing Contours\nCall is:\n" << argv[0] << " image\n\n";
+    return -1;
+  }
+
+  cv::threshold(img, img_edge, 128, 255, cv::THRESH_BINARY);
+  cv::imshow("Image after threshold", img_edge);
+  vector< vector< cv::Point > > contours;
+  vector< cv::Vec4i > hierarchy;
+
+  cv::findContours(
+    img_edge,
+    contours,
+    hierarchy,
+    cv::RETR_LIST,
+    cv::CHAIN_APPROX_SIMPLE
+  );
+  cout << "\n\nHit any key to draw the next contour, ESC to quit\n\n";
+  cout << "Total Contours Detected: " << contours.size() << endl;
+
+  vector<int> sortIdx(contours.size());
+  vector<float> areas(contours.size());
+  for( int n = 0; n < (int)contours.size(); n++ ) {
+    sortIdx[n] = n;
+    areas[n] = contourArea(contours[n], false);
+  }
+
+  // sort contours so that the largest contours go first
+  //
+  std::sort( sortIdx.begin(), sortIdx.end(), AreaCmp(areas ));
+
+  for( int n = 0; n < (int)sortIdx.size(); n++ ) {
+    int idx = sortIdx[n];
+    cv::cvtColor( img, img_color, cv::COLOR_GRAY2BGR );
+    cv::drawContours(
+      img_color, contours, idx,
+      cv::Scalar(0,0,255), 2, 8, hierarchy,
+      0 // Try different values of max_level, and see what happens
+    );
+    cout << "Contour #" << idx << ": area=" << areas[idx] <<
+      ", nvertices=" << contours[idx].size() << endl;
+    cv::imshow(argv[0], img_color);
+    int k;
+    if( (k = cv::waitKey()&255) == 27 )
+      break;
+  }
+  cout << "Finished all contours\n";
+
+  return 0;
+}
diff --git a/example_14-03.cpp b/example_14-03.cpp
new file mode 100644
index 0000000..1dd3d23
--- /dev/null
+++ b/example_14-03.cpp
@@ -0,0 +1,51 @@
+// Example 14-3. Drawing labeled connected components
+
+#include <algorithm>
+#include <iostream>
+#include<opencv2/opencv.hpp>
+
+using namespace std;
+
+int main(int argc, char* argv[]) {
+
+  cv::Mat img, img_edge, labels, img_color, stats;
+
+  // load image or show help if no image was provided
+  if( argc != 2
+  || (img = cv::imread( argv[1], cv::IMREAD_GRAYSCALE )).empty()
+  ) {
+    cout << "\nExample 8_3 Drawing Connected componnents\n" \
+    << "Call is:\n" <<argv[0] <<" image\n\n";
+    return -1;
+  }
+
+  cv::threshold(img, img_edge, 128, 255, cv::THRESH_BINARY);
+  cv::imshow("Image after threshold", img_edge);
+
+  int i, nccomps = cv::connectedComponentsWithStats (
+  img_edge, labels,
+  stats, cv::noArray()
+  );
+  cout << "Total Connected Components Detected: " << nccomps << endl;
+
+  vector<cv::Vec3b> colors(nccomps+1);
+  colors[0] = cv::Vec3b(0,0,0); // background pixels remain black.
+  for( i = 1; i <= nccomps; i++ ) {
+    colors[i] = cv::Vec3b(rand()%256, rand()%256, rand()%256);
+    if( stats.at<int>(i-1, cv::CC_STAT_AREA) < 100 )
+    colors[i] = cv::Vec3b(0,0,0); // small regions are painted with black too.
+  }
+  img_color = cv::Mat::zeros(img.size(), CV_8UC3);
+  for( int y = 0; y < img_color.rows; y++ )
+    for( int x = 0; x < img_color.cols; x++ )
+    {
+      int label = labels.at<int>(y, x);
+      CV_Assert(0 <= label && label <= nccomps);
+      img_color.at<cv::Vec3b>(y, x) = colors[label];
+    }
+
+  cv::imshow("Labeled map", img_color);
+  cv::waitKey();
+  return 0;
+}
+
diff --git a/example_14-04.cpp b/example_14-04.cpp
new file mode 100644
index 0000000..c2b148f
--- /dev/null
+++ b/example_14-04.cpp
@@ -0,0 +1,54 @@
+// Example 14-4. Using the shape context distance extractor
+
+#include <algorithm>
+#include <iostream>
+#include <string>
+
+#include "opencv2/opencv.hpp"
+
+using namespace std;
+using namespace cv;
+
+static vector<Point> sampleContour( const Mat& image, int n=300 ) {
+
+  vector<vector<Point> > _contours;
+  vector<Point> all_points;
+  findContours(image, _contours, RETR_LIST, CHAIN_APPROX_NONE);
+  for (size_t i=0; i <_contours.size(); i++) {
+    for (size_t j=0; j <_contours[i].size(); j++)
+      all_points.push_back( _contours[i][j] );
+
+    // If too little points, replicate them
+    //
+    int dummy=0;
+    for (int add=(int)all_points.size(); add<n; add++)
+      all_points.push_back(all_points[dummy++]);
+
+    // Sample uniformly
+    random_shuffle(all_points.begin(), all_points.end());
+    vector<Point> sampled;
+    for (int i=0; i<n; i++)
+      sampled.push_back(all_points[i]);
+    return sampled;
+  }
+}
+
+int main(int argc, char** argv) {
+
+  string path = "../data/shape_sample/";
+  int indexQuery = 1;
+
+  Ptr<ShapeContextDistanceExtractor> mysc = createShapeContextDistanceExtractor();
+
+  Size sz2Sh(300,300);
+  Mat img1=imread(argv[1], IMREAD_GRAYSCALE);
+  Mat img2=imread(argv[2], IMREAD_GRAYSCALE);
+  vector<Point> c1 = sampleContour(img1);
+  vector<Point> c2 = sampleContour(img2);
+  float dis = mysc->computeDistance( c1, c2 );
+  cout << "shape context distance between " <<
+    argv[1] << " and " << argv[2] << " is: " << dis << endl;
+
+  return 0;
+
+}
diff --git a/faceScene.jpg b/faceScene.jpg
new file mode 100644
index 0000000..670592d
Binary files /dev/null and b/faceScene.jpg differ
diff --git a/faceTemplate.jpg b/faceTemplate.jpg
new file mode 100644
index 0000000..1006387
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diff --git a/fruits.jpg b/fruits.jpg
new file mode 100644
index 0000000..a89b84a
Binary files /dev/null and b/fruits.jpg differ
diff --git a/shape_sample/1.png b/shape_sample/1.png
new file mode 100644
index 0000000..f473cb4
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diff --git a/shape_sample/10.png b/shape_sample/10.png
new file mode 100644
index 0000000..46283ca
Binary files /dev/null and b/shape_sample/10.png differ
diff --git a/shape_sample/11.png b/shape_sample/11.png
new file mode 100644
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