Abstract:

A practical neural network model of morphological filters with its optimal parameters training algorithm is proposed. For application to the infrared motional image target detection, a dynamic training algorithm, namely Morphological Adjusted-Weight Neural Network (MANN), is applied to the detecting process using the asymptotic shrinking error and appropriate network weights adjusting. Experimental results show that the algorithm has an invariant property with respect to the shift, scale and rotation of the moving target in the continuing detection of moving targets.

Key words: mathematical morphology, image analyzing, target detection, neural net work, optimization computing