Task-guided segmentation and its application in real-time IR ship recognition
Task-guided segmentation and its application in real-time IR ship recognition
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DOI：
10.1117/12.441487
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发表时间：
2001-09
期刊：
影响因子：
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通讯作者：
Yuehuang Wang;Nanzhi Zeng;Tianxu Zhang
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文献类型：
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作者：
Yuehuang Wang;Nanzhi Zeng;Tianxu Zhang
本文对现有的分割方法进行了总结。大津方法适合于实时实现，但对目标尺寸敏感。如果目标与背景相比太小，它总是不能被分割。针对这一问题，提出了一种任务引导的分割方法。在该模型中，利用注意力的思想，在当前任务的指导下进行图像分割。提出了一种任务引导的分割模型，并将其应用于实时红外舰船识别。实验结果证明了该方法的有效性。
In this paper, existing segmentation approaches are summarized. The Otsu method is found to fit for real-time implementation but sensitive to target size. If target is too small compared with the background, it always cannot be segmented. To solve such problem, a task-guided segmentation is proposed. In such model, with the idea of attention, image segmentation is processed under the guidance of tasks at hand. A model of task-guided segmentation is proposed and is applied in real-time IR ship recognition. Experimental results demonstrated the effectiveness of the approach proposed.