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Trail-dependent intelligent scissors based on multi-scale image segmentation

机译:基于多尺度图像分割的Trail依赖智能剪刀

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Image segmentation is a very important topic in computer vision. However, due to the large variation of image content, fully automatic image segmentation for general applications is still an open problem. Therefore, our goal is to develop an interactive image segmentation toot that can accurately extract the desired object boundaries with minimal human efforts. In this paper, we propose a new trail-dependent intelligent scissors, which let the user interactively extract desired object boundaries based on multi-scale image segmentation. By utilizing the information contained in the trail of the cursor's motion, which somewhat implies the intention of the human operator, our intelligent scissors can allow the user to extract a desired object boundary with less mouse-clicking, and hence is more user-friendly. This is the major advantage of our new intelligent scissors. Another advantage is that our intelligent scissors permits the user to trace the object boundary with less tension by utilizing the coarse-to-fine region boundries provided by multi-scale image segmentation. Our experiments have demonstrated that the new interactive segmentation tool requires less human efforts than the previously available tools.
机译:图像分段是计算机视觉中的一个非常重要的主题。然而,由于图像内容的较大变化,一般应用的全自动图像分割仍然是一个开放的问题。因此,我们的目标是开发一个交互式图像分割嘟嘟,可以用最小的人力努力来准确提取所需的对象边界。在本文中,我们提出了一种新的依赖智能剪刀,这让用户基于多尺度图像分割来交互地提取所需的目标边界。通过利用所包含的游标运动中包含的信息,这有些意思是人类运营商的意图,我们的智能剪刀可以允许用户用更少的鼠标点击提取所需的对象边界,因此更用户友好。这是我们新的智能剪刀的主要优势。另一个优点是,我们的智能剪刀允许用户通过利用多尺度图像分割提供的粗略区域边界来跟踪对象边界的较少张力。我们的实验表明,新的交互式分割工具比以前可用的工具更少的人力努力。

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