一种结合视觉显著性和线段强度的位置提取方法

Xiaoyu Chang, Min Wang, Gang Wang, Feng Gao
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引用次数: 0

摘要

针对现有研究中位置样本选择困难、位置识别人工依赖程度高的问题,本文提出了一种结合视觉显著性和线段强度的位置提取方法。为了验证本文提出的算法的有效性,对两幅图像进行了测试,并通过定量指标对准确率进行了评价。可以发现,两个位置的IoU (Intersection of Union)分别为0.6658和0.5319,均大于0.5,表明本研究提出的无监督提取方法是有效的。位置的查全率均大于0.83,说明该方法提取的位置的遗漏率较低,均在17%以内。本研究提出了一种无需训练样本即可有效提取目标的无监督位置提取方法,为快速无监督目标识别提供了可靠的技术手段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Position Extraction Method Combining Visual Saliency and Line Segment Intensity
To solve the problems of difficult selection of position samples and high manual dependence of position recognition in most existing researches, this paper proposes a position extraction method combining visual saliency and line segment intensity. In order to verify the effectiveness of the algorithm proposed in this study, the two images were tested, and evaluated the accuracy through quantitative indicators. It can be found that the IoU (Intersection of Union) of the two positions are 0.6658 and 0.5319, respectively, which are all greater than 0.5, indicating the effectiveness of the unsupervised extraction method proposed in this research. The recall rate of the position was all greater than 0.83, indicating that the omission rate of the extracted positions by this method was relatively low, all within 17%. In this study, an unsupervised position extraction method is proposed, which can effectively extract target without training samples, and provides a reliable technical means for rapid unsupervised target recognition.
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