RECOGNITION AND CLUSTERING OF CONNECTED COMPONENTS IN BI-LEVEL IMAGES

Methods, apparatus and data structures for identifying, processing and interpreting bi-level connected component objects found within graphic images. The disclosure includes methods for generating lumped graph representations (4100) of the targeted objects (3000) and for using these to recognize the objects as known objects in a reference dictionary (10010). To implement this method, a bi-level connected component object (3000) is identified within an image (2010) and the object is represented as a plurality of pixel runs (3100-3430) of a given binary value. A lumped graph representation (4100) which captures characteristic topological features of the object is created based upon the connectivity data of the pixel runs in the object. This information is then used to recognize the object (3000) by comparing the lumped graph feature vectors with feature vectors of known objects stored in the dictionary (10010). Optionally, the dictionary (10010) can be updated such that newly recognized objects can be added to the dictionary (10010) for future recognition purposes.