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首页> 外文期刊>Journal of Infrared, Millimeter and Terahertz Waves >Building Recognition Based on Geometric Model in FLIR Image Sequences
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Building Recognition Based on Geometric Model in FLIR Image Sequences

机译:FLIR图像序列中基于几何模型的建筑物识别

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摘要

In this paper, we propose a novel method for building recognition from forward looking infrared (FLIR) image sequences with clutter in the background for automatic target recognition (ATR). In the first phase, dynamic feature space is defined, and camera model and multi-scale characteristic views model that are used to predict model's features based on 3D object reference model are introduced. In the second phase, the original image is preprocessed using morphological grayscale filters that respond to the size, shape and orientation of object to suppress the background that contains the non-stationary nature and man-made objects of the clutter image. In the following phase, segmentation for the result of image preprocessing is used to obtain regions of interest (ROIs), and features extraction of ROIs and matching retain ROIs that are closest to predicted features. Lastly, the object is identified by fusing the line features. Experiment results show the algorithm can recognize the object from FLIR image sequences with a complicated background.
机译:在本文中,我们提出了一种新的方法,该方法用于根据前瞻性红外(FLIR)图像序列在背景中具有杂波的自动目标识别(ATR)来进行识别。在第一阶段,定义了动态特征空间,并介绍了用于基于3D对象参考模型预测模型特征的摄像机模型和多尺度特征视图模型。在第二阶段,使用形态灰度滤镜对原始图像进行预处理,这些滤镜响应对象的大小,形状和方向,以抑制包含杂乱图像的非平稳性质和人造对象的背景。在接下来的阶段中,使用图像预处理结果的分割来获得感兴趣区域(ROI),并提取ROI的特征并进行匹配,保留最接近预测特征的ROI。最后,通过融合线特征来识别对象。实验结果表明,该算法可以从背景复杂的FLIR图像序列中识别出物体。

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