Building Recognition Based on Geometric Model in FLIR Image Sequences

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.