How to draw contour in OpenCV

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by l.rohitharohitha2001@gmail.com dot icon Updated: Oct 4, 2023

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OpenCV stands for "Open-Source Computer Vision Library." This computer vision and image processing library is open-source.


It provides tools for tasks related to computer vision and image analysis. Intel created OpenCV in 1999. It is now a widely used library in computer vision. Contours are lines that connect points of the same color or brightness. Tasks such as object detection and image segmentation rely heavily on computer vision.  

Types of Contours  

  • Circular Contours  
  • Rectangular Contours  
  • Triangular Contours  
  • Polygonal Contours  
  • Elliptical Contours  
  • Curved Contours  
  • Arbitrary Contours  
  • Hierarchical Contours.  

Key points of the essay

  1. OpenCV for Contour Extraction: OpenCV is a computer vision library. It is open-source and used for image processing tasks. The Contours() function in OpenCV is a powerful tool. It can find and extract contours from images.  
  2. Image Preprocessing: Before finding contours, we need to preprocess the image. To convert the image, first make it grayscale. Then, smooth it and set a threshold.  
  3. Threshold: You can find the value in three ways: manual, automatic, or adaptive.  
  4. Contour retrieval & approximation: Estimating how accurate shapes affect accuracy and details.  
  5. Contour Filtering: After you get the shapes, keep the ones that are the right size and length. This helps to keep only the relevant contours.  
  6. Benefits of Contour Extraction: Extracting contours is very important in computer vision. It helps find objects and divide images. It helps analyze shapes.  
  7. Visual Feedback and Experimentation: To see the shapes, look at the steps in between. Try different ways and settings.  


You must find contours to work with OpenCV for computer vision and image processing. Contour detection has many benefits and is important in different applications.