Object recognition by matching symbolic edge graphs

We present an object recognition system based on symbolic graphs with object corners as vertices and outlines as edges. Corners are determined in a robust way by a multiscale combination of an operator modeling cortical end-stopped cells. Graphs are constructed by line-following between corners. Model matching is then done by finding subgraph isomorphisms in the image graph. The complexity is reduced by adding labels to corners and edges. The choice of labels makes the recognition system invariant under translation, rotation, and scaling