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Algorithm of Ground Object Detection with Modified SURF Method by Using Morphological Features

机译:基于形态特征的改进SURF方法检测地面物体

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Two approaches are combined into one algorithm in order to reach better accuracy of ground object detection and tracking. Blob analysis provides the separation of detected object by morphological criterion (mostly minimum area threshold is used) and is used to determine the region of interest for further selection of feature points. Points are detected and described by Speed-Up Robust Feature descriptors method. Due to combination the amount of processing information is decrease that leads to increasing of not only the accuracy but also efficiency of algorithm.
机译:两种方法组合成一种算法,以达到更好的地面物体检测和跟踪精度。斑点分析可通过形态学标准(大多数情况下使用最小面积阈值)将检测到的物体分开,并用于确定感兴趣区域以进一步选择特征点。通过加速鲁棒特征描述符方法检测并描述点。由于结合,处理信息的量减少,这不仅导致算法的准确性而且导致效率的提高。

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