In the Ubuntu 16.04 64bit Required dependencies are the followings:
sudo apt-get install libopencv-dev python-opencvpkg-config --modversion opencvIf the version is shown, then we’re good to rock with opencv.
With CMake (Don’t forget to add CMakeLists.txt)
cmake_minimum_required(VERSION 2.8)
project( <project_name> )
find_package( OpenCV REQUIRED )
add_executable( <project_name> <project_name>.cpp )
target_link_libraries( <project_name> ${OpenCV_LIBS} )With g++ and flags for opencv libraries
g++ lab1-2.cpp `pkg-config --cflags --libs opencv`Note: The default image matrix is three-channel type, we have to do the gray scale conversion, only ⅓ of the image will be processed.
Mat input_img = imread(argv[1]);
//since the bgr channel is used for default action, then the BGR 3 channel image must be converted to GREY channel
cvtColor(input_img, input_img, CV_BGR2GRAY);
Mat output_img = input_img.clone();
histogram_equal(input_img, output_img);Histogram Equalization Function:
oid histogram_equal(Mat& input, Mat& output)
{
vector<int> hash_distribution;
vector<double> intensity_cdf;
hash_distribution.resize(256);
intensity_cdf.resize(256);
for(int i=0;i<input.rows;i++)
{
for(int j=0;j<input.cols;j++)
{
hash_distribution[(int) input.at<uchar>(i,j)]++;
}
}
//search the maxium value
int max_value = 0, cnt=0;
double cumulative_cnt = 0.0f;
for(int i=0;i<hash_distribution.size();i++)
{
if(hash_distribution[i]!=0)
{
max_value = max(max_value, i);
cumulative_cnt += (double) hash_distribution[i] / (double)(input.rows * input.cols);
cnt += hash_distribution[i];
intensity_cdf[i] = cumulative_cnt;
}
}
for(int i=0;i<input.rows;i++)
{
for(int j=0;j<input.cols;j++)
{
output.at<uchar>(i,j) = (intensity_cdf[input.at<uchar>(i,j)] * max_value );
}
}
}Laplace sharpening function:
void mask(Mat& input, Mat& output) {
// write down your code here
for (int i = 0; i<output.rows; i++) {
for (int j = 0; j<output.cols; j++) {
int temp = (-4)*(input.at<uchar>(i, j));
if (i - 1 >= 0)
temp += input.at<uchar>(i - 1, j);
if (j - 1 >= 0)
temp += input.at<uchar>(i, j - 1);
if (i + 1 < output.rows)
temp += input.at<uchar>(i + 1, j);
if (j + 1 < output.cols)
temp += input.at<uchar>(i, j + 1);
if (temp > 255)
output.at<uchar>(i, j) = 255;
else if (temp < 0)
output.at<uchar>(i, j) = 0;
else
output.at<uchar>(i, j) = temp;
}
}
}Otsu threshold function:
float sum = 9999;
int bestThreshold;
vector<int> histo(256,0);
findHistogram(input, histo); // a function to find histogram
for(int i=0;i<256;i++){
vector<int> small; // vector of smaller pixels
vector<int> big; // vector of bigger pixels
for(int j=0;j<i;j++){
for(int k=0;k<histo[j];k++)
small.push_back(j);
}
for(int j=i;j<256;j++){
for(int k=0;k<histo[j];k++)
big.push_back(j);
}
float averageS = average(small);
float averageB = average(big);
float newSum = small.size() * variance(small, averageS, small.size()) + big.size() * variance(big, averageB, big.size());
if (sum == 9999){
sum = newSum;
bestThreshold = i;
}
else if(newSum <= sum){
sum = newSum;
bestThreshold = i;
}
}
for(int i=0;i<input.rows;i++){
for(int j=0;j<input.cols;j++){
if(input.at<uchar>(i,j) < bestThreshold)
output.at<uchar>(i,j) = 0;
else
output.at<uchar>(i,j) = 255;
}
}
cout << "Threshold: " << bestThreshold << endl;connected components function:
void connectedComponents(Mat& input, Mat& output){
for(int i=0;i<input.rows;i++){
for(int j=0;j<input.cols;j++){
if(input.at<uchar>(i,j) < 200){
input.at<uchar>(i,j) = 0;
}
else
input.at<uchar>(i,j) = 255;
}
}
int label = 50;
for(int i=0;i<input.rows;i++){
for(int j=0;j<input.cols;j++){
if(input.at<uchar>(i,j) == 255){
input.at<uchar>(i,j) = label;
findNext(i, j, label, input.rows, input.cols, input);
label += 10;
}
}
}
for(int i=0;i<input.rows;i++){
for(int j=0;j<input.cols;j++){
if(input.at<uchar>(i,j) != 0){
//cout << input.at<uchar>(i,j) << endl;
int label2 = input.at<uchar>(i,j);
output.at<Vec3b>(i,j)[0] = (label2%45 * 531)% 255;
output.at<Vec3b>(i,j)[1] = 255 - label2;
output.at<Vec3b>(i,j)[2] = (label2%30 * 35)% 255;
}
else{
output.at<Vec3b>(i,j)[0] = 0;
output.at<Vec3b>(i,j)[1] = 0;
output.at<Vec3b>(i,j)[2] = 0;
}
}
}
}FindNext function to do find next unchanged pixel:
void findNext(int i, int j, int label, int rows, int cols, Mat& input){
if(i-1 >= 0){
if(input.at<uchar>(i-1,j) == 255){
input.at<uchar>(i-1,j) = label;
findNext(i-1, j, label, input.rows, input.cols, input);
}
if(j-1 >= 0){
if(input.at<uchar>(i-1,j-1) == 255){
input.at<uchar>(i-1,j-1) = label;
findNext(i-1, j-1, label, input.rows, input.cols, input);
}
}
if(j+1 < cols){
if(input.at<uchar>(i-1,j+1) == 255){
input.at<uchar>(i-1,j+1) = label;
findNext(i-1, j+1, label, input.rows, input.cols, input);
}
}
}
if(i+1 < rows){
if(input.at<uchar>(i+1,j) == 255){
input.at<uchar>(i+1,j) = label;
findNext(i+1, j, label, input.rows, input.cols, input);
}
if(j-1 >= 0){
if(input.at<uchar>(i+1,j-1) == 255){
input.at<uchar>(i+1,j-1) = label;
findNext(i+1, j-1, label, input.rows, input.cols, input);
}
}
if(j+1 < cols){
if(input.at<uchar>(i+1,j+1) == 255){
input.at<uchar>(i+1,j+1) = label;
findNext(i+1, j+1, label, input.rows, input.cols, input);
}
}
}
if(j-1 >= 0){
if(input.at<uchar>(i,j-1) == 255){
input.at<uchar>(i,j-1) = label;
findNext(i, j-1, label, input.rows, input.cols, input);
}
}
if(j+1 < cols){
if(input.at<uchar>(i,j+1) == 255){
input.at<uchar>(i,j+1) = label;
findNext(i, j+1, label, input.rows, input.cols, input);
}
}
}