Image co-segmentation using dual active contours
Image co-segmentation using dual active contours
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DOI：
10.1016/j.asoc.2018.02.034
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
Ashish Ghosh;Sanmoy Bandyopadhyay
中科院分区：
文献类型：
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作者：
Ashish Ghosh;Sanmoy Bandyopadhyay
本文提出了一种同时分割一对图像（共分割）以提取共同目标的新算法。采用双几何活动轮廓模型实现了图像的共分割。在给定的图像中，（物体的）两个轮廓同时初始化和演化。当轮廓线向图像中常见物体的边界移动时，能量值会降低。允许轮廓演变，直到内外轮廓在对象边界重合。所形成的结果图像称为共分割图像。该方法在20个基准数据集上进行了评估，并与最先进的方法进行了比较。结果表明，所提方法的性能优于对比方法。
In this article a novel algorithm is proposed to segment a pair of images simultaneously (co-segmentation) for extracting common objects. The task of co-segmentation has been performed using the dual geometric active contour model. Both the contours (of the objects) are initialized and evolved simultaneously in the given images. As the contours proceed towards the boundary of the common object(s) present in the images, energy value gets reduced. The contours are allowed to evolve until both the inner and the outer contours coincide at the object boundary. The resultant images formed are known as the co-segmented images. The proposed approach is evaluated on 20 benchmark datasets and compared with the state-of-the-art methods. Results show that the performance of the proposed method is better than the compared methods.