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Knowledge-based hierarchical method for detecting regions of interest

机译:基于知识的层次结构感兴趣区域检测方法

摘要

A knowledge-based hierarchical method for detecting regions of interests (ROIs) uses prior knowledge of the targets and the image resolution in detecting ROIs. The result produces ROIs that contain only one target that is completely enclosed within the ROI. The detected ROI can conform to the shape of the target even if the target is of irregular shape. Furthermore, the method works well with images that contain connected targets or targets broken into pieces. The method is not sensitive to contrast levels and is robust to noise. Thus, this method effectively detects ROIs in common real world imagery that has a low resolution without costly processing while providing fast and robust results.
机译:用于检测感兴趣区域(ROI)的基于知识的分层方法使用目标的先验知识和图像分辨率来检测ROI。结果产生的ROI仅包含一个完全封闭在ROI中的目标。即使目标是不规则形状,所检测到的ROI也可以符合目标的形状。此外,该方法适用于包含相连目标或破碎目标的图像。该方法对对比度水平不敏感,并且对噪声具有鲁棒性。因此,该方法可有效检测具有低分辨率的普通现实世界图像中的ROI,而无需进行昂贵的处理,同时提供快速而可靠的结果。

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