Connected Components Labeling (CCL) represents an essential part of many Image Processing and Computer Vision pipelines. Given its relevance on the field, it has been part of most cutting-edge Computer Vision libraries. In this paper, all the algorithms included in the OpenCV during the years are reviewed, from sequential to parallel/GPU-based implementations. Our goal is to provide a better understanding of what has changed and why one algorithm should be preferred to another both in terms of memory usage and execution speed.
Quest for Speed: The Epic Saga of Record-Breaking on OpenCV Connected Components Extraction / Bolelli, Federico; Allegretti, Stefano; Grana, Costantino. - 13374:(2022), pp. 107-118. (Intervento presentato al convegno International Conference on Image Analysis and Processing, Binary is the New Black (and White) Workshop tenutosi a Lecce nel May 24) [10.1007/978-3-031-13324-4_10].
Quest for Speed: The Epic Saga of Record-Breaking on OpenCV Connected Components Extraction
Federico Bolelli
;Stefano Allegretti;Costantino Grana
2022-01-01
Abstract
Connected Components Labeling (CCL) represents an essential part of many Image Processing and Computer Vision pipelines. Given its relevance on the field, it has been part of most cutting-edge Computer Vision libraries. In this paper, all the algorithms included in the OpenCV during the years are reviewed, from sequential to parallel/GPU-based implementations. Our goal is to provide a better understanding of what has changed and why one algorithm should be preferred to another both in terms of memory usage and execution speed.
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