Robot Academy Robot Academy
Sign In
Learn Resources Donate About Sign In

Search Results for: centroid

Region Features

lesson

When it comes to describing a blob we can do more than just area, centroid position and bounding box. By looking at second order moments we can compute an ellipse that has the same moments of inertia as the blob, and we can use its aspect ratio and orientation to describe the shape and orientation […]

Multiple Image Regions

lesson

For a binary image that contains multiple blobs we must first transform it using connectivity analysis or region labeling. Then we can describe each of the blobs in the scene we first need to transform the image using connectivity analysis. Each of the blobs can then be described in terms of its area, centroid position, […]

Image Region

lesson

If we look at a binary image we can easily see distinct regions, that is, sets of pixels the same color as their neighbours. We call these blobs and they’re an important way of achieving an object rather than pixel view of the scene. We can describe these blobs by their area, centroid position, bounding […]

Summary of Feature Extraction

lesson

Let’s recap the important points from the topics we have covered about image features, blobs, connectivity analysis, and blob parameters such as centroid position, area, bounding box, moments, equivalent ellipse, and perimeter.

Proudly supported by:

  • Queensland University of Technology
  • Australian Centre for Robotic Vision
  • IEEE Robotics and Automation Society
Join our Facebook group About Resources Donate Copyright Terms of use

© QUT Robot Academy