殷凯. 基于显著性的目标自动分割算法[J]. 微电子学与计算机, 2013, 30(8): 67-70.
引用本文: 殷凯. 基于显著性的目标自动分割算法[J]. 微电子学与计算机, 2013, 30(8): 67-70.
YIN Kai. Saliency-Based Automatic Object Segmentation Algorithm[J]. Microelectronics & Computer, 2013, 30(8): 67-70.
Citation: YIN Kai. Saliency-Based Automatic Object Segmentation Algorithm[J]. Microelectronics & Computer, 2013, 30(8): 67-70.

基于显著性的目标自动分割算法

Saliency-Based Automatic Object Segmentation Algorithm

  • 摘要: 针对半监督分割方法的缺点,提出了一个基于显著性的目标自动分割算法。选取效率最好的频谱残差方法作为显著性方法,对显著图得到的粗分割区域分别进行腐蚀和膨胀处理来自动获得目标标签和背景标签。基于最大相似性的区域合并方法在标签的帮助下,目标可以有效地从背景中提取。对自然图像实验的数据结果证实了该方法能够自动可靠地从复杂的背景中提取目标。

     

    Abstract: To overcome the drawback of the semi-supervised segmentation methods,we propose a new saliency based automatic natural object segmentation method.We choose the spectral residual method as the saliency method for its low cost.We make erosion and dilation on the coarse segmentation region to get the object label and background label automatically.By maximal similarity based region merging with the help of labels,the object can be effectively extracted from the background.Extensive experiments results on a large variety of natural images confirm that our framework can reliably and automatically extract the object from the complex background.

     

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