This work proposes a new automatic target classifier, based on a combined neural networks’ system, by ISAR image processing. The novelty introduced in our work is twofold. We first present a novel automatic classification procedure, and then we discuss an improved multimedia processing of ISAR images for automatic object detection. The classifier, composed by a combination of 20 feed-forward artificial neural networks, is used to recognize aircraft targets extracted from ISAR images. A multimedia processing by two recently introduced image processing techniques is exploited to improve the shape and features extraction process. Performance analysis is carried out in comparison with conventional multimedia techniques and standard detectors. Numerical results obtained from wide simulation trials evidence the efficiency of the proposed method for the application to automatic aircraft target recognition.
Benedetto, F., Riganti, F., Laudani, A., & Albanese, G. (2012). Automatic Aircraft Target Recognition by ISAR Image Processing based on Neural Classifier. International Journal of Advanced Computer Science and Applications, 3(8). https://doi.org/10.14569/ijacsa.2012.030816