Computationally efficient, one-pass algorithm for morphological filters

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 (ASFn) 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.

► Efficient, zero-latency, low-memory algorithm for serial morphological filters. ► Allows parallel execution of the operators despite their serial data dependence. ► Allows to obtain the results of an arbitrarilly long serial filter in a constant time. ► On dedicated HW allows to achieve unrivalled performances for large images.