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OPENCV – PYTHON | Retrieval Modes in Contour Detection | RETR EXTERNAL, LIST, TREE | Hierarchy

In the enchanting world of computer vision, contours stand as the backbone of shape analysis and object detection. These outlines, or contours, trace the boundaries of objects within an image, paving the way for advanced image processing and analysis. Before we dive into the intricacies of contour retrieval modes, let’s first understand what contours truly represent.

 

Flow of Article:

  1. Understanding the Contours 
  2. Retr External Contour retrieval
  3. List Contour Retrieval
  4. Tree Contour Retrieval

 

Video Explanation :

 

Understanding Contours:

In OpenCV, contours are a fundamental concept representing the boundaries of objects in an image. These boundaries are a sequence of points that form the shape of the object. Whether detecting shapes, recognizing objects, or analyzing structures, contours serve as the foundation for a myriad of computer vision applications.

Now, let’s embark on a journey to explore contour retrieval modes, each offering a unique perspective on how these boundaries are organized.

 

1. RETR_EXTERNAL: Extracting Outer Contours

  • Use Case: When you want to extract only the outermost contours.
  • Function: cv2.RETR_EXTERNAL retrieves only the extreme outer contours, discarding any nested contours.
  • Code Reference:

contours, hierarchy = cv2.findContours(image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

2. RETR_LIST: Unveiling All Contours in a List

  • Use Case: Ideal when you need a flat list of all contours without any hierarchical organization.
  • Function: cv2.RETR_LIST retrieves all contours without creating a nested hierarchy.
  • Code Reference:

contours, hierarchy = cv2.findContours(image, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)

3. RETR_TREE: Embracing Hierarchical Contours

  • Use Case: When contours are organized hierarchically, revealing relationships between parent and child contours.
  • Function: cv2.RETR_TREE retrieves all contours and reconstructs a full hierarchy of nested contours.
  • Code Reference:

contours, hierarchy = cv2.findContours(image, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

Decoding the Hierarchy:

The hierarchy information, often obtained alongside contours, unveils the structural relationships between contours. It signifies which contours are parents, children, or share the same parent, providing valuable insights into the image’s organization.

In your OpenCV-Python projects, understanding these contour retrieval modes empowers you to tailor your contour detection strategy based on the specific demands of your application. Whether you seek simplicity with RETR_EXTERNAL, a flat contour list with RETR_LIST, or hierarchical insights with RETR_TREE, contours and their retrieval modes open the door to endless possibilities in the realm of computer vision. Happy contour crafting!

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