1. Lecture 3 More programming in OpenCV Slides by: Clark F. Olson

2. Accessing pixels The most general way to access pixels is a template method: image.at (row, col) This returns a reference, so it can be an lvalue or an rvalue. For color images, we need to say which channel: image.at (row, col)[channel]// channel is 0,1,2 Note that channel 0 is blue, channel 1 is green, channel 2 is red.

3. Accessing pixels Creating the image with a specific type allows shorter code. Mat_ greyImage = imread(“grey.jpg”); uchar greylevel = greyImage(row, col); Mat_ colorImage = imread(“color.jpg”); colorImage(row, col)[0] = newBlueValue;

4. Accessing pixels Pixels can also be accessed using pointer manipulation. This is the fastest, but not necessarily the best. int perRow = image.cols * image.channels(); for (int r = 0; r < image.rows; r ++) { uchar *currentRow = image.ptr (r); // ok for grey or color for (int c = 0; c < perRow; c++) { currentRow[c] = 255 – currentRow[c]; // invert pixel color }

5. Accessing pixels A couple of notes: Acquiring a new pointer for each row is generally necessary, since the rows may be padded. uchar *currentRow = image.ptr (r); // ok for grey or color Can also use pointer arithmetic: * currentRow++ = 255 – *currentRow; // invert pixel color

6. Accessing pixels One more way to access the pixels is using iterators. This will give you all of the pixels in raster order. Mat_ ::iterator it = image.begin (); Mat_ ::iterator itend = image.end (); for ( ; it != itend; ++it) for (int c = 0; c < 3; c++) (*it)[c] = 256 - (*it)[c];