SPmat: A Framework and Data Representation for Binary Image Processing

Abstract

We propose an optimized framework for binary image processing, characterized by a highly bit-packed representation of pixels and their square neighbourhood. The Super-Packed (SPmat) representation for binary images enables the easy use of bit-wise computations for developing fast processing algorithms, such as: morphology, contours, run-length, and thinning, in a unified framework. With several experiments, we show that the aforementioned algorithms can be consistently sped-up, and outperform by a large margin available software implementations. The software package is freely available on github at the url https://github.com/fpeder/spmat to support reproducibility.