Documentation Index Fetch the complete documentation index at: https://mintlify.com/opencv/opencv/llms.txt
Use this file to discover all available pages before exploring further.
Image as Matrix In OpenCV, images are represented as Mat objects - multi-dimensional arrays where:
Grayscale images : Single-channel 2D arrays (CV_8UC1)Color images : Multi-channel 2D arrays (typically CV_8UC3 for BGR)Pixel values : Usually 8-bit unsigned integers (0-255)
Image Properties Dimensions Mat img = imread ( "image.jpg" ); int height = img . rows ; // Image height int width = img . cols ; // Image width int channels = img . channels (); // Number of channels Size size = img . size (); // Size(width, height)
Data Type int type = img . type (); // e.g., CV_8UC3 int depth = img . depth (); // e.g., CV_8U bool empty = img . empty (); // Check if image is empty
Color Spaces OpenCV uses BGR (not RGB) as the default color order:
// Load color image (BGR by default) Mat bgr = imread ( "image.jpg" ); // Access BGR values Vec3b pixel = bgr . at < Vec3b > (y, x); uchar blue = pixel [ 0 ]; uchar green = pixel [ 1 ]; uchar red = pixel [ 2 ];
Most other libraries use RGB order. Always convert when interfacing with external systems.
See Color Spaces for conversion details.
Pixel Access Single Pixel // Grayscale image uchar intensity = grayImg . at < uchar > (y, x); // Color image Vec3b color = colorImg . at < Vec3b > (y, x); color [ 0 ] = 255 ; // Modify blue channel colorImg . at < Vec3b > (y, x) = color;
Efficient Row Access for ( int i = 0 ; i < img . rows ; i ++ ) { uchar * row = img . ptr < uchar > (i); for ( int j = 0 ; j < img . cols ; j ++ ) { row [j] = /* process pixel */ ; } }
Multi-Channel Access for ( int i = 0 ; i < img . rows ; i ++ ) { Vec3b * row = img . ptr < Vec3b > (i); for ( int j = 0 ; j < img . cols ; j ++ ) { row [j][ 0 ] = /* blue */ ; row [j][ 1 ] = /* green */ ; row [j][ 2 ] = /* red */ ; } }
Image Operations Creating Images // Create blank image Mat img ( 480 , 640 , CV_8UC3 , Scalar ( 0 , 0 , 0 )); // Black // Create from size Mat img = Mat :: zeros ( Size ( 640 , 480 ), CV_8UC3); Mat img = Mat :: ones ( Size ( 640 , 480 ), CV_8UC1);
Copying Images // Shallow copy (shares data) Mat img2 = img1; // Deep copy Mat img2 = img1 . clone (); img1 . copyTo (img2); // Copy with mask img1 . copyTo (img2, mask);
Image ROI // Select rectangular region Rect roi ( x , y , width , height ); Mat region = img (roi); // Modify ROI (affects original) region = Scalar ( 0 , 255 , 0 ); // Fill with green
Channel Operations Split and Merge // Split into channels vector < Mat > channels; split (img, channels); // channels[0]=B, channels[1]=G, channels[2]=R // Merge channels Mat merged; merge (channels, merged);
// Extract blue channel Mat blueChannel; extractChannel (img, blueChannel, 0 ); // Set channel to zero Mat channels [ 3 ]; split (img, channels); channels [ 0 ] = Mat :: zeros ( img . size (), CV_8UC1); merge (channels, 3 , img); // Blue channel now zero
Image I/O Reading Images // Read color image Mat img = imread ( "image.jpg" ); // Read grayscale Mat gray = imread ( "image.jpg" , IMREAD_GRAYSCALE); // Read with alpha channel Mat rgba = imread ( "image.png" , IMREAD_UNCHANGED);
Writing Images // Save image imwrite ( "output.jpg" , img); // Save with parameters vector < int > params = {IMWRITE_JPEG_QUALITY, 95 }; imwrite ( "output.jpg" , img, params);
Common Patterns Convert to Grayscale Mat gray; cvtColor (img, gray, COLOR_BGR2GRAY);
Resize Image Mat resized; resize (img, resized, Size ( 320 , 240 )); // Scale by factor resize (img, resized, Size (), 0.5 , 0.5 );
Crop Image Rect cropRegion ( x , y , width , height ); Mat cropped = img (cropRegion). clone ();
Use Pointer Access Prefer ptr<T>() over at<T>() for pixel-level operations
Check Continuity Continuous matrices enable faster processing
Avoid Copies Use references and ROI instead of cloning
Batch Operations Use OpenCV functions instead of pixel loops
See Also 