Pattern matching using morphological probing

In this paper, we introduce two new morphological transforms for pattern matching in gray scale images. They rely on a profiling approach and are defined in the context of mathematical morphology. The first transform allows to detect all occurrences of a single pattern in an image, which justifies the name SOMP (single object matching using probing). It is shown to have the properties of a metric and therefore returns a measure of similarity between the search image and the reference pattern. Other properties relative to noise and computation time are highlighted. The second transform MOMP (multiple objects matching using probing) offers the ability to locate multiple patterns simultaneously. It is particularly suited to the detection of objects varying in size and with noisy distortion. Some results are presented for both transforms.