We use some simple flat rigid shapes to introduce the general principles of model-based recognition, including pose estimation, model matching and verification. We also introduce methods for finding the straight line segments that make up the part's boundary.
We introduce a simple flat rigid part recognition system that is based on matching part edges to a geometric model. This will also require estimating the reference frame transformation that maps the model onto the image data.
First we find the edge points that surround the part, by analyzing a binary image.
We next turn the boundary edge points into a more compact set of straight line segments.
Then we match those straight line segments to a rigid geometric model using the Interpretation Tree model matching algorithm.
Because the matching and pose estimation phases can produce spurious matches and poses, we introduce a verification step that eliminates bad hypotheses.