Title :
Multidimensional image analysis and mathematical morphology
Author_Institution :
Electr. & Comput. Eng., State Univ. of New York, Buffalo, NY, USA
Abstract :
Summary form only given. Multidimensional operators based on mathematical morphology have been proposed for image segmentation. Mathematical morphology is basically a set theory. It provides the concept of a structuring element to probe the image with arbitrary geometric patterns, in order to capture the topological properties of the image. The classical operators have been extended to multidimensions. A morphological approach to scale-space filtering has been developed. Multiscale morphological openings that nonlinearly smooth the image without blurring the features (edges) have been used. The approach has been formulated within the framework of alternating sequential filters (ASF)
Keywords :
filtering and prediction theory; picture processing; set theory; alternating sequential filters; arbitrary geometric patterns; image segmentation; mathematical morphology; multidimensional operators; multiscale morphological openings; scale-space filtering; set theory; topological properties; Humans; Image analysis; Image segmentation; Magnetic analysis; Magnetic resonance; Morphology; Multidimensional systems; Probes; Set theory; Tail;
Conference_Titel :
Multidimensional Signal Processing Workshop, 1989., Sixth
Conference_Location :
Pacific Grove, CA
DOI :
10.1109/MDSP.1989.97120