Neural-Network and Log-Polar Sampling Based Associative Pattern Recognizer for Aircraft Images

신경 회로망과 Log-Polar Sampling 기법을 사용한 항공기 영상의 연상 연식

In this paper, we aimed to develop associative pattern recognizer based on neural network for aircraft identification. For obtaining invariant feature space description of an object regardless of its scale change and rotation, Log-polar sampling technique recently developed partly due to its similarity to the human visual system was introduced with Fourier transform post-processing. In addition to the recognition results, image recall was associatively performed and also used for the visualization of the recognition reliability. The multilayer perceptron model was learned by backpropagation algorithm.