Skip to main content

SURF keypoints using a camera



#include <stdlib.h>
#include <stdio.h>
#include <math.h>
#include <string.h>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/imgproc/imgproc_c.h>
#include <opencv2/video/tracking.hpp>
#include <iostream>
#include <vector>

using namespace std;
int main(int argc, char** argv)
{
CvMemStorage* storage = cvCreateMemStorage(0);
cvNamedWindow("Object", 1);
int key = 0;
static CvScalar colors[] =
{
{{0,0,255}},
{{0,128,255}},
{{0,255,255}},
{{0,255,0}},
{{255,128,0}},
{{255,255,0}},
{{255,0,0}},
{{255,0,255}},
{{255,255,255}}
};

CvCapture* capture = cvCreateCameraCapture(0);
CvMat* prevgray = 0, *image = 0, *gray =0;
while( key != 'q' )
{
int firstFrame = gray == 0;
IplImage* frame = cvQueryFrame(capture);
if(!frame)
break;
if(!gray)
{
image = cvCreateMat(frame->height, frame->width, CV_8UC1);
}
cvCvtColor(frame, image, CV_BGR2GRAY);
CvSeq *imageKeypoints = 0, *imageDescriptors = 0;
int i;

//Extract SURF points by initializing parameters
CvSURFParams params = cvSURFParams(500, 1);
cvExtractSURF( image, 0, &imageKeypoints, &imageDescriptors, storage, params );
printf("Image Descriptors: %d\n", imageDescriptors->total);

//draw the keypoints on the captured frame
for( i = 0; i < imageKeypoints->total; i++ )
{
CvSURFPoint* r = (CvSURFPoint*)cvGetSeqElem( imageKeypoints, i );
CvPoint center;
int radius;
center.x = cvRound(r->pt.x);
center.y = cvRound(r->pt.y);
radius = cvRound(r->size*1.2/9.*2);
cvCircle( frame, center, radius, colors[0], 1, 8, 0 );
}
cvShowImage( "Object", frame );

cvWaitKey(30);
}
cvDestroyWindow("Object");
return 0;
}

Labels:

Comments

Post a Comment

Popular posts from this blog

Computing Entropy of an image (CORRECTED)

entropy is a measure of the uncertainty associated with a random variable. basically i want to get a single value representing the entropy of an image. 1. Assign 255 bins for the range of values between 0-255 2. separate the image into its 3 channels 3. compute histogram for each channel 4. normalize all 3 channels unifirmely 5. for each channel get the bin value (Hc) and use its absolute value (negative log is infinity) 6. compute Hc*log10(Hc) 7. add to entropy and continue with 5 until a single value converges 5. get the frequency of each channel - add all the values of the bin 6. for each bin get a probability - if bin 1 = 20 bin 2 = 30 then frequency is 50 and probability is 20/50 and 30/50 then compute using shannon formula  REFERENCE: http://people.revoledu.com/kardi/tutorial/DecisionTree/how-to-measure-impurity.htm class atsHistogram { public:     cv::Mat DrawHistogram(Mat src)     {      ...
6 comments
Read more

Blob Detection, Connected Component (Pure Opencv)

Connected-component labeling (alternatively connected-component analysis, blob extraction, region labeling, blob discovery, or region extraction) is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic. Connected-component labeling is not to be confused with segmentation. i got the initial code from this URL: http://nghiaho.com/?p=1102 However the code did not compile with my setup of OpenCV 2.2, im guessing it was an older version. so a refactored and corrected the errors to come up with this Class class atsBlobFinder     {     public:         atsBlobFinder()         {         }         ///Original Code by http://nghiaho.com/?p=1102         ///Changed and added commments. Removed Errors     ...
2 comments
Read more

Region of interest selection ROI

#include <stdlib.h> #include <stdio.h> #include <math.h> #include <string.h> #include<opencv2\opencv.hpp> #include <opencv2\highgui\highgui.hpp> int main(int argc, char *argv[]) { CvCapture *capture = 0; IplImage *frame = 0; int key = 0; /* initialize camera */ capture = cvCaptureFromCAM( 0 ); /* always check */ if ( !capture ) { printf("Cannot open initialize webcam!\n" ); exit(0); } /* create a window for the video */ cvNamedWindow( "result", CV_WINDOW_AUTOSIZE ); while( key != 'q' ) { /* get a frame */ frame = cvQueryFrame( capture ); /* always check */ if( !frame ) break; /* sets the Region of Interest*/ cvSetImageROI(frame, cvRect(150, 50, 150, 250)); /* create destination image */ IplImage *img2 = cvCreateImage(cvGetSize(frame), frame->depth, frame->nChannels); /* * do the main processing with subimage here. * in this example, we simply invert the subimage ...
Post a Comment
Read more