Fast algorithms for morphological operations using run-length encoded binary images

TL;DR

This paper introduces fast algorithms for morphological operations on run-length encoded binary images, leveraging skeleton extraction and distance tables to improve computational efficiency and enable skipping unnecessary pixel analysis.

Contribution

The paper proposes novel algorithms that efficiently perform erosions and dilations on RLE binary images using skeleton and distance table techniques, with source code provided.

Findings

Algorithms outperform existing methods in speed.

Preprocessing reduces computation by trimming images.

Experimental results validate efficiency gains.

Abstract

This paper presents innovative algorithms to efficiently compute erosions and dilations of run-length encoded (RLE) binary images with arbitrary shaped structuring elements. An RLE image is given by a set of runs, where a run is a horizontal concatenation of foreground pixels. The proposed algorithms extract the skeleton of the structuring element and build distance tables of the input image, which are storing the distance to the next background pixel on the left and right hand sides. This information is then used to speed up the calculations of the erosion and dilation operator by enabling the use of techniques which allow to skip the analysis of certain pixels whenever a hit or miss occurs. Additionally the input image gets trimmed during the preprocessing steps on the base of two primitive criteria. Experimental results show the advantages over other algorithms. The source code of our algorithms is available in C++.