FAST MORPHOLOGY HARDWARE USING LARGE-SIZED STRUCTURING ELEMENT

Mathematical morphology is one of the data processing methods that is extremely useful for image processing and has many applications, such as, noise elimination, shape description, texture analysis, and so on. The mathematical base of morphological processing is dilation and erosion which are described by set analysis and can be expressed in logical AND, OR notation. Localized parallel processing including morphological processing is not suitable to Neumann architecture because of the memory access bottleneck which makes it hard to achieve the high throughout data processing required in applications such as video image processing. Also the cytocomputer aimed at fast image processing has a drawback in that it. can handle only very small structuring elements. In this paper, first, an algorithm is presented which accelerates morphological image processing. Next, the algorithm to design a specialized hardware which processes the real-time video image is implemented and finally, an application of this specialized hardware for medical use is described.