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水平集曲线演化快速提取足迹轮廓

Fast Footprint Contour Extraction by Curve Evolution via Level Sets

  • 摘要: 提出空间多分辨分析方法,通过分析图像行列方向能量投影的分布,将图像划分为大小不均匀的子块,根据图像的总体结构特征和局部细节特征自适应地调整子块大小,并以各子块的灰度均值作为新图像基元像素的灰度值,实现图像压缩.水平集曲线演化方法在压缩图像上进行,使得被处理的数据量大大减少,从而缩短了轮廓提取的时间,提高了算法的实用性.与边缘检测方法或直接水平集曲线演化方法相比较表明,该方法能够以较少的运算量获取较高的足迹轮廓提取准确度.

     

    Abstract: A method based on spatial multi-scale analysis is put forward.Based on the energy projection distribution on rows and columns of an image,the image is divided into subimages with different size,which is adaptively adjusted according both the holistic features and the local features.By assigning the average of gray levels in each subimage as the gray level of the corresponding element in a new image,the original image is compressed.Curve evolution method via level sets is then applied to the newly compressed image,and the data size is reduced largely.In addition,the time of extracting contours is shortened substantially in turn and the practicability of the method is enhanced significantly.The proposed method is used to extract footprint contours and is shown experimentally to outperform the direct edge detection method as well as the curve evolution method basing on level sets in terms of computational cost and the detection veracity.

     

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