devansh20la's profile - activity

Thank you for the advice. I wasn't planning to recognize objects before but then I thought of extending the project to recognition of objects. My opencv folder has xml files only for full body eyes face smile license plate I couldn't find one for cars.I tried it with few other cascades available online for cars but no luck.

The aspect ratio of the object changes as the take turns around the junction the ROI works well but I am detecting car with a red bounding box and bikes with blue. Is there a way to detect contour in a region and then set the color for the entire time the object is in the frame?

My project requires me to track road traffic parameters from a stationary camera.

I have tracked moving features using optical flow farneback algorithm, created a binary image with white blob on the moving object. Now, my want to classify them as cars or motorbikes.

I tried using the blob area but the problem is the contour/blob area increases or decreases as the object comes closer or away from the camera.

Any suggestion on how can I tackle this issue?

how to do it?

http://postimg.org/image/vndfjtzg5/

double alpha; /**< Simple contrast control */

int beta; /**< Simple brightness control */

int main( int argc, char** argv )

{ Mat image = imread( argv[1] );

Mat new_image = Mat::zeros( image.size(), image.type() );

cout<<"* Enter the alpha value [1.0-3.0]: ";cin>>alpha; cout<<"* Enter the beta value [0-100]: ";cin>>beta;

/// Do the operation new_image(i,j) = alpha*image(i,j) + beta

for( int y = 0; y < image.rows; y++ )

{ for( int x = 0; x < image.cols; x++ )

{ for( int c = 0; c < 3; c++ )
     {

new_image.at<vec3b>(y,x)[c] =saturate_cast<uchar>( alpha*( image.at<vec3b>(y,x)[c] ) + beta );

}

}

}

namedWindow("Original Image", 1);

namedWindow("New Image", 1);

imshow("Original Image", image);

imshow("New Image", new_image);

waitKey();

return 0;

}