一种基于不确定系数的图像序列变化比较方法

Ruzhang Zhao, Yajun Fang, B. Horn
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引用次数: 0

摘要

对于图像序列变化信息的识别,大多数研究都集中在单个图像序列的变化检测上,很少有研究考虑两个不同图像序列之间的变化水平比较。此外,大多数研究都需要对图像信息进行详细的检测,例如目标检测。基于不确定系数(UC),提出了一种用于两幅图像序列变化比较的创新方法“CCUC”。该方法计算效率高,实现简单。这种变化比较源于视频监控系统。有限的屏幕数量和大量的监控摄像机要求视频或图像序列按变化级别排序。我们通过将其应用于两个公开可用的图像序列来演示这种新方法。结果表明,该方法能够区分序列的不同变化程度。
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A Simple Change Comparison Method for Image Sequences Based on Uncertainty Coefficient
For identification of change information in image sequences, most studies focus on change detection in one image sequence, while few studies have considered the change level comparison between two different image sequences. Moreover, most studies require the detection of image information in details, for example, object detection. Based on Uncertainty Coefficient(UC), this paper proposes an innovative method “CCUC” for change comparison between two image sequences. The proposed method is computationally efficient and simple to implement. The change comparison stems from video monitoring system. The limited number of provided screens and a large number of monitoring cameras require the videos or image sequences ordered by change level. We demonstrate this new method by applying it on two publicly available image sequences. The results are able to show the method can distinguish the different change level for sequences.
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