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Journal articles
Computationally efficient, one-pass algorithm for morphological filters
Abstract : Many useful morphological filters are built as long concatenations of erosions and dilations: openings, closings, size distributions, sequential filters, etc. This paper proposes a new algorithm implementing morphological dilation and erosion of functions. It supports rectangular structuring element, runs in linear time w.r.t. the image size and constant time w.r.t. the structuring element size, and has minimal memory usage. It has zero algorithm latency and processes data in stream. These properties are inherited by operators composed by concatenation, and allow their efficient implementation. We show how to compute in one pass an Alternate Sequential Filter (ASF(n)) regardless the number of stages n. This algorithm opens the way to such time-critical applications where the complexity and memory requirements of serial morphological operators represented a bottleneck limiting their usability. (C) 2011 Elsevier Inc. All rights reserved.
Keywords :
Algorithm
Mathematical morphology
Nonlinear filters
Real-time implementation
Serial filters
Streaming
Computationally efficient
Constant time
Efficient implementation
Image sizes
Linear time
Memory requirements
Memory usage
Morphological dilation
Morphological filters
Morphological operator
Nonlinear filter
One-pass
Real-time implementations
Sequential filter
Structuring element
Time-critical applications
Cited literature [40 references]
https://hal-upec-upem.archives-ouvertes.fr/hal-00692897
Contributor : Eva Dokladalova Connect in order to contact the contributor
Submitted on : Friday, July 5, 2013 - 3:11:31 PM
Last modification on : Saturday, January 15, 2022 - 3:57:39 AM
Long-term archiving on: : Sunday, October 6, 2013 - 3:05:10 AM
Contributor : Eva Dokladalova Connect in order to contact the contributor
Submitted on : Friday, July 5, 2013 - 3:11:31 PM
Last modification on : Saturday, January 15, 2022 - 3:57:39 AM
Long-term archiving on: : Sunday, October 6, 2013 - 3:05:10 AM
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