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PEL: A Predictive Edge Linking algorithm

机译:PEL:一种预测性边缘链接算法

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摘要

We propose an edge linking algorithm that takes as input a binary edge map generated by a traditional edge detection algorithm and converts it to a set of edge segments; filling in one pixel gaps in the edge map, cleaning up noisy edge pixel formations and thinning multi-pixel wide edge segments in the process. The proposed edge linking algorithm walks over the edge map based on the predictions generated from its past movements; thus the name Predictive Edge Linking (PEL). We evaluate the performance of PEL both qualitatively using visual experiments and quantitatively within the precision-recall framework of the Berkeley Segmentation Dataset and Benchmark (BSDS 300). Both visual experiments and quantitative evaluation results show that PEL greatly improves the modal quality of binary edge maps produced by traditional edge detectors, and takes a very small amount of time to execute making it suitable for real-time image processing and computer vision applications. (C) 2016 Elsevier Inc. All rights reserved.
机译:我们提出了一种边缘链接算法,该算法以传统边缘检测算法生成的二进制边缘图为输入,并将其转换为一组边缘段。填补边缘图中的一个像素间隙,在此过程中清理嘈杂的边缘像素结构并细化多像素宽边缘段。所提出的边缘链接算法基于从其过去的运动产生的预测来遍历边缘地图。因此,名称为“预测性边缘链接(PEL)”。我们使用视觉实验定性地评估了PEL的性能,并在伯克利细分数据集和基准(BSDS 300)的精确召回框架内定量评估了PEL的性能。视觉实验和定量评估结果均表明,PEL极大地改善了传统边缘检测器生成的二进制边缘图的模态质量,并且只需花费很少的时间即可执行,使其适用于实时图像处理和计算机视觉应用。 (C)2016 Elsevier Inc.保留所有权利。

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