Pattern matching using the blur hit - miss transform

The usefulness of the hit-miss transform (HMT) and related transforms for pattern matching in document image applications is examined. Although the HMT is sensitive to the types of noise found in scanned images, including both boundary and random noise, a simple extension, the Blur HMT, is relatively robust. The noise immunity of the Blur HMT derives from its ability to treat both types of noise together, and to remove them by appropriate dilations. In analogy with the Hausdorff metric for the distance between two sets, metric generalizations for special cases of the Blur HMT are derived. Whereas Hausdorff uses both directions of the directed distances between two sets, a metric derived from a special case of the Blur HMT uses just one direction of the directed distances between foreground and background components of two sets. For both foreground and background, the template is always the first of the directed sets. A less restrictive metric generalization, where the disjoint foregro...

• Type: Journal
• Year: 2000
• Where: JEI
• Authors: Dan S. Bloomberg, Luc Vincent
• Keywords: Blur HMT, Image, JEI 2000, Metric