- OpenCV Tutorial
- OpenCV - Home
- OpenCV - Overview
- OpenCV - Environment
- OpenCV - Storing Images
- OpenCV - Reading Images
- OpenCV - Writing an Image
- OpenCV - GUI
- Types of Images
- OpenCV - The IMREAD_XXX Flag
- Reading an Image as Grayscale
- OpenCV - Reading Image as BGR
- Image Conversion
- Colored Images to GrayScale
- OpenCV - Colored Image to Binary
- OpenCV - Grayscale to Binary
- Drawing Functions
- OpenCV - Drawing a Circle
- OpenCV - Drawing a Line
- OpenCV - Drawing a Rectangle
- OpenCV - Drawing an Ellipse
- OpenCV - Drawing Polylines
- OpenCV - Drawing Convex Polylines
- OpenCV - Drawing Arrowed Lines
- OpenCV - Adding Text
- Filtering
- OpenCV - Bilateral Filter
- OpenCV - Box Filter
- OpenCV - SQRBox Filter
- OpenCV - Filter2D
- OpenCV - Dilation
- OpenCV - Erosion
- OpenCV - Morphological Operations
- OpenCV - Image Pyramids
- Sobel Derivatives
- OpenCV - Sobel Operator
- OpenCV - Scharr Operator
- Transformation Operations
- OpenCV - Laplacian Transformation
- OpenCV - Distance Transformation
- Camera and Face Detection
- OpenCV - Using Camera
- OpenCV - Face Detection in a Picture
- Face Detection using Camera
- Geometric Transformations
- OpenCV - Affine Translation
- OpenCV - Rotation
- OpenCV - Scaling
- OpenCV - Color Maps
- Miscellaneous Chapters
- OpenCV - Canny Edge Detection
- OpenCV - Hough Line Transform
- OpenCV - Histogram Equalization
- OpenCV Useful Resources
- OpenCV - Quick Guide
- OpenCV - Useful Resources
- OpenCV - Discussion
Discuss OpenCV
OpenCV is a cross-platform library using which we can develop real-time computer vision applications. It mainly focuses on image processing, video capture and analysis including features like face detection and object detection. In this tutorial, we explain how you can use OpenCV in your applications.
Advertisements
To Continue Learning Please Login
Login with Google