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Target Segmentation Algorithm Based on Toboganning Method in Infrared Images

机译:基于红外图像中烟花宁方法的目标分割算法

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This paper suggests an efficient target segmentation algorithm in 3 steps for infrared (IR) images. First step is the segmentation as homogenous region on IR image. And, second step is merging of region without meaningful boundary between segmented regions. At the final step, region, which is considered as meaningless due to composition with minute region, is merged by consideration of similarity with surrounding regions. In this paper, 3 kinds of dams, energy dam, sponge dam, valve dam, are proposed to induce efficient merging for geometrical features. In addition, we propose the mask for merging of segmented region from gradation. Through this, we propose the efficient image segmentation algorithm which is robust from over-segmentation and over-merging.
机译:本文提出了一种高效的目标分割算法,用于红外(IR)图像的3个步骤。第一步是IR图像上作为同质区域的分段。并且,第二步是在分段区域之间没有有意义的边界的区域合并。在最后一步,通过考虑与周围地区的相似性来合并,该区域被认为是由于具有分钟区域的组成而被认为是毫无意义的。在本文中,提出了3种水坝,耗能器,海绵坝,阀门坝,促使几何特征的有效合并。此外,我们提出了从渐变中合并分段区域的掩模。通过这一点,我们提出了高效的图像分割算法,其来自过分分割和过度合并的强大。

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