基于视觉注意机制和水平集方法的红外海面目标检测与识别

发布时间：2018-03-24 23:34

  本文选题：视觉注意　切入点：水平集方法　出处：《红外》2016年11期

【摘要】：针对传统红外目标检测与识别方法所存在的问题,即其处理过程总是盲目地对全图进行耗时搜索,提出了一种基于视觉注意机制和水平集方法的红外海面目标检测与识别方法。首先,搜索原始图像中的显著性区域,并以获胜点的形式表示它们。接着,基于所得到的显著性区域,自动初始化水平集函数,并使演化过程朝着期望的目标轮廓方向挺进,直至演化过程到达最终的平衡状态。最后,针对远距离(近距离)成像时的输入数据,给出检测结果(基于不变矩和神经网络框架的识别结果)。对真实红外海面目标进行的实验证实了本文方法的有效性。
[Abstract]:Aiming at the problems of traditional infrared target detection and recognition methods, that is, the processing process always blindly carries out the time-consuming search of the whole image. In this paper, a method of infrared sea surface target detection and recognition based on visual attention mechanism and level set method is proposed. Firstly, the salient regions in the original image are searched, and they are represented in the form of winning points. Based on the obtained salience region, the level set function is automatically initialized, and the evolution process moves towards the desired target profile until the evolution process reaches the final equilibrium state. For the input data of long range (short range) imaging, the detection results (based on the invariant moment and neural network framework) are given. Experiments on the real infrared sea surface target show the effectiveness of the proposed method.
【作者单位】： 93501部队17分队;电子科技大学航空航天学院;空军第一航空学院航空弹药教研室;
【基金】：中央高校基本科研业务费(ZYGX2015KYQD032)
【分类号】：TP391.41
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本文编号：1660581