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Model-based segmentation of FLIR images

机译:基于模型的FLIR图像分割

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摘要

The use of gray-scale intensities together with the edge information present in a forward-looking infrared (FLIR) image to obtain a precise and accurate segmentation of a target is presented. A model of FLIR images based on gray-scale and edge information is incorporated in a gradient relaxation technique which explicitly maximizes a criterion function based on the inconsistency and ambiguity of classification of pixels with respect to their neighbors. Four variations of the basic technique which provide automatic selection of thresholds to segment FLIR images are considered. These methods are compared, and several examples of segmentation of ship images are given.
机译:提出了使用灰度强度以及前视红外(FLIR)图像中存在的边缘信息来获得目标的精确分割。基于灰度和边缘信息的FLIR图像模型被并入梯度松弛技术中,该技术基于像素相对于其相邻像素的分类的不一致性和歧义性,显着最大化了准则函数。考虑了提供自动选择阈值以分割FLIR图像的基本技术的四个变体。比较了这些方法,并给出了分割船舶图像的几个示例。

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