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Binary morphological processing operations have been shown to be useful in a range of industrial inspection applications. These operations have been available in two forms: As software-based operations on general-purpose algorithm development workstations, such as Bruce Batchelor's SUSIE and its many descendants, and as hardware-based operations on dedicated "morphology engines." Obstacles to wider use of these methods include • Limited familiarity with binary morphological processing techniques on the part of general users, • The slow operation of software-based implementations, and • The relatively high initial cost of fast special-purpose binary morphological processing hardware. This paper describes another alternative: A near-real-time implementation of binary morphological processing as part of a very large set of operations on a moderately-priced general-purpose image processing and algorithm development workstation. The workstation is based on commercially-available image processing boards, and provides a high-level operator interface. With this system, the speed depends on the size of the structuring element, but migration to real-time implementations using the same hardware family is straightforward. This implementation allows arbitrary specification of the final structuring element, with no constraints as to symmetry, connectedness, concavities, holes, etc. This eliminates one of the obstacles to the use of complex structuring elements on some dedicated morphological processing machines -- the need to find a set of simple "primitives" which, when applied sequentially, will yield the desired structuring element. The nature of the implementation also allows for a new possibility: By a change in one register, operation is converted from a strict binary morphology into "fuzzy" morphology (not grey-level morphology), in which the user can specify a "percentage fit" of structuring element to image. By this means, the structuring element can still be made to "fit" even in the presence of some "noise" pixels, without the need for separate noise-removal steps. This greatly increases the robustness and practicality of morphological methods in "real world" industrial inspection applications.
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