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 23-27 May 2022) [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
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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