In color based object detection project, one can detect the color object. User needs to change the trackbar values,

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Introduction

In color based object detection project, one can detect the color object. User needs to change the trackbar values, As trackbar changes the value, the color space filters with HSV filtered image processed bounding rectangle. Bounding rectangle (MAX 2000 (RECT AREA) in project) detects the contourArea (2000) and draws the rectangle.

Sample - One

In this RED color spotted. then using bounding rectangle the STOP SIGN detected. LowerH:168, UpperH:256, LowerS:175, UpperS: 256, LoweV:0, UpperV:256 By manipulating these values, one can detect the color based any object.

Sample - Two

In this YELLOW color spotted. Then using bounding rectangle the SIGN detected. LowerH:0, UpperH:75, LowerS:139, UpperS: 256, LoweV:132, UpperV:198 By manipulating these values, one can detect the color based any object.

Sample - Three

In this WHITE color spotted, then using bounding rectangle the SIGN detected. LowerH:0, UpperH:256, LowerS:0, UpperS: 256, LoweV:0, UpperV:61 By manipulating these values, one can detect the color based any object.

Code

Here is the complete code for color based object detection using the opencv. The following code has been completed using Visual Studio 2008 and Opencv Libraries.

Process of Setting up the Visual Studio - Click to View

• Process of Visual Studio 2008 Setup For OpenCV Libraries.

User Libraries and Study Materials - Click to View

• Image Processing
• High GUI
• Operation With Images
• Cascade Classifier Training
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#include "opencv/cv.h"
#include "opencv/highgui.h"
#include "opencv2/opencv.hpp"
#include "opencv2/core/core.hpp"
#include "opencv2/opencv.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "iostream"
#include "stdio.h"
#include "string"
#include <stdlib.h>

using namespace cv;
using namespace std;

int lowerH=168;
int upperH=256;

int lowerS=175;
int upperS=256;

int lowerV=0;
int upperV=256;  

IplImage* frame = 0 ;
IplImage* frame2 = 0 ;
IplImage* imgHSV = 0 ;
IplImage* imgThresh = 0 ;

//vector<vector<Point> > contours;
//vector<Vec4i> hierarchy;

void draw_conture(IplImage * temp)
{
  /*
   cv::Mat tempm(temp,true);  
   findContours( tempm , contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE, cv::Point(0, 0) );
   vector<vector<cv::Point> > contours_poly( contours.size() );
   vector<Rect> boundRect( contours.size() );
   vector<float>area( contours.size() );

   for(  int i = 0; i < contours.size(); i++ )
   {
       approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
      boundRect[i] = boundingRect( Mat(contours_poly[i]) ) ;
      area[i]= contourArea(Mat(contours_poly[i]));
   }

   const CvScalar color=CV_RGB(0x00,0xFF,0x00);                        
   for( int i = 0; i< contours.size(); i++ )
   {                
     if (area[i]>1000)
         rectangle(tempm, boundRect[i].tl(), boundRect[i].br(), color, 1, 1, 0 );
   }
  */ 

   CvSeq* contour;  //hold the pointer to a contour
   CvSeq* result;     //hold sequence of points of a contour
   CvMemStorage *storage = cvCreateMemStorage(0); //storage area for all contours

   cvFindContours(temp, storage, &contour, sizeof(CvContour), 
		CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE, cvPoint(0,0));

   for (; contour != 0; contour = contour->h_next)
   {  
       result = cvApproxPoly(contour, sizeof(CvContour), 
		storage, CV_POLY_APPROX_DP, cvContourPerimeter(contour)*0.02, 0);                
       CvRect rect = cvBoundingRect(contour, 0); //extract bounding box for current contour
       if( cvContourArea(result, CV_WHOLE_SEQ,0) >= 1000 )
       {
         //cvDrawContours(frame, contour, CV_RGB(0,0,255), CV_RGB(0,0,255), 2, 1, 8, cvPoint(0, 0));
         frame2 = cvCreateImage(cvGetSize(frame), frame->depth, frame->nChannels);
         cvCopy(frame, frame2);
         cvRectangle(frame2, cvPoint(rect.x, rect.y), 
		cvPoint(rect.x+rect.width, rect.y+rect.height), CV_RGB(0,0,255),2, 8, 0);  
       }
   }  
   cvShowImage("Object Color Range", frame2);
}

#pragma region trackbar

void on_trackbar1(int position)
{   
    lowerH = position;       
    cvInRangeS(imgHSV, cvScalar(lowerH,lowerS,lowerV), cvScalar(upperH,upperS,upperV),imgThresh);
    cvShowImage("Object Detected", imgThresh);
    draw_conture(imgThresh);   
}

void on_trackbar2(int position)
{
    upperH = position;
    cvInRangeS(imgHSV, cvScalar(lowerH,lowerS,lowerV), cvScalar(upperH,upperS,upperV),imgThresh);
    cvShowImage("Object Detected", imgThresh);
    draw_conture(imgThresh);   
}

void on_trackbar3(int position)
{
    lowerS = position;   
    cvInRangeS(imgHSV, cvScalar(lowerH,lowerS,lowerV), cvScalar(upperH,upperS,upperV),imgThresh);
    cvShowImage("Object Detected", imgThresh);
    draw_conture(imgThresh);
}

void on_trackbar4(int position)
{
    upperS = position;   
    cvInRangeS(imgHSV, cvScalar(lowerH,lowerS,lowerV), cvScalar(upperH,upperS,upperV),imgThresh);
    cvShowImage("Object Detected", imgThresh);
    draw_conture(imgThresh);
}

void on_trackbar5(int position)
{
    lowerV = position;
    cvInRangeS(imgHSV, cvScalar(lowerH,lowerS,lowerV), cvScalar(upperH,upperS,upperV),imgThresh);
    cvShowImage("Object Detected", imgThresh);
    draw_conture(imgThresh);
}

void on_trackbar6(int position)
{
    upperV = position;
    cvInRangeS(imgHSV, cvScalar(lowerH,lowerS,lowerV), cvScalar(upperH,upperS,upperV),imgThresh);
    cvShowImage("Object Detected", imgThresh);
    draw_conture(imgThresh);
}

#pragma endregion trackbar

int main()
{
  cvNamedWindow("Object Color Range",1);
  cvNamedWindow("Object Detected",1);

  cvCreateTrackbar("LowerH", "Object Detected", &lowerH, 256, on_trackbar1);
  cvCreateTrackbar("UpperH", "Object Detected", &upperH, 256, on_trackbar2);
  cvCreateTrackbar("LowerS", "Object Detected", &lowerS, 256, on_trackbar3);
  cvCreateTrackbar("UpperS", "Object Detected", &upperS, 256, on_trackbar4);
  cvCreateTrackbar("LowerV", "Object Detected", &lowerV, 256, on_trackbar5);
  cvCreateTrackbar("UpperV", "Object Detected", &upperV, 256, on_trackbar6);
  frame  = cvLoadImage("stop.jpg",1);  

  imgHSV = cvCreateImage(cvGetSize(frame), IPL_DEPTH_8U, 3 ) ;  
  imgThresh = cvCreateImage(cvGetSize(imgHSV),IPL_DEPTH_8U, 1);  
  cvCvtColor(frame, imgHSV, CV_BGR2HSV);    
  cvInRangeS(imgHSV, cvScalar(lowerH,lowerS,lowerV), cvScalar(upperH,upperS,upperV),imgThresh); 

  cvShowImage("Object Detected", imgThresh);
  cvShowImage("Object Color Range", frame);

  draw_conture(imgThresh);
  cvWaitKey(0);

  cvReleaseImage(&imgHSV);
  cvReleaseImage(&imgThresh);
  cvReleaseImage(&frame);
 

  cvDestroyAllWindows();
  return 0;
}

Point of Interest

• Learn how to set up OpenCV with Visual Studio
• Learn how to process the image
• Learn how to filter the color space
• Learn how to use bounding rectangle
• Learn how to detect the object based on color
• Learn how to use opencv trackbar

References

• OpenCV Home
• Wikipedia - OpenCV
• Documentation - OpenCV
• OpenCV - Books
• Downloads