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    <p>One solution would be to apply dilation and erosion and find all contours that are smaller than X-pixels and fill them with white color:</p> <pre><code>int main() { // Load the image as a Grayscale Mat image = imread("image.jpg", CV_LOAD_IMAGE_GRAYSCALE); // Threshold the image image = image &gt; 120; // Create bigger image with image width and height + 10 pixels Mat image_big = Mat::zeros( image.size().height + 10, image.size().width + 10, CV_8UC1 ); // Set bigger image to be all white image_big.setTo(255); Mat image_big_copy; // This may vary, you must find it for yourself // Dilate image 4 times and erode once dilate(image, image, Mat(), Point(-1,-1), 4); erode(image, image, Mat(), Point(-1,-1)); // Copy image in the center of bigger image so you left 5px around image blank/white // Create a new ROI that points to center of the bigger image Mat image_big_roi = image_big( Rect(Point(5, 5), Size(image.size())) ); // Copy image to the bigger image ROI addWeighted(image_big_roi, 0., image, 1., 0., image_big_roi); // Create a data copy of image_big image_big.copyTo(image_big_copy); // Find all contours in a given image and store them in contours vector&lt;vector&lt;Point&gt; &gt; contours; findContours(image_big_copy, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE); for( int i = 0; i &lt; contours.size(); i++ ) { // This is your condition to filter out unwanted contours etc. // For every contour if its area is bigger/smaller than the sum of pixels if ( fabs(contourArea(Mat(contours[i]))) &lt; 800 ) { // Fill a contour with white color drawContours(image_big, contours, i, Scalar(255), CV_FILLED); } } imshow("Image original", image); imshow("Image edited", image_big); waitKey(0); return 0; } </code></pre> <p>Original image:</p> <p><img src="https://i.stack.imgur.com/fCsWs.jpg" alt="enter image description here"></p> <p>After:</p> <p><img src="https://i.stack.imgur.com/SOopS.jpg" alt="enter image description here"></p>
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    1. POCrop image into pieces and then join, is that possible using OpenCV?
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