A novel approach for template matching by nonorthogonal image expansion

A novel approach to template matching using nonorthogonal expansion with template-similar basis functions is described. The results show that this expansion is superior in comparison with the normalized-correlation (matched-filtering) approach. It is proved that the expansion can be efficiently implemented by restoration filtering and that this method yields optimal discriminative signal-to-noise ratio. It is further proved that the nonorthogonal expansion can be performed with an almost unlimited variety of basis functions. Results show that the expansion approach has definite advantages over correlation, especially in conditions of noise and severe occlusion. When recognition is required in audio, radar, or sonar signals, where the principle of occlusion is replaced by superposition, correlation techniques are even more ineffective and the expansion approach yields better results