Fast algorithms for morphological operations using run-length encoded binary images
This work addresses a domain-specific problem in image processing for applications requiring fast morphological operations, but it is incremental as it builds on existing RLE techniques.
The paper tackled the problem of efficiently computing erosions and dilations on run-length encoded binary images with arbitrary structuring elements, resulting in algorithms that use skeleton extraction and distance tables to speed up calculations and show advantages in experimental results.
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++.