Translation and scale-invariant pattern recognition based on the Hamming network. (1st January 2003) - Huang, An-Chyau; Ko, Shen-Chin
The purpose of this paper is to develop a position and scale-invariant pattern recognition system based on the Hamming network (HN). The input image is processed by a feature extraction network to calculate the exact position and dimension of the pattern feature. An associate memory network is the designed to map the obtained dimension information to its corresponding HN weight matrix. With its weight matrix determined, the HN maps the input image into a proper class. Since all network parameters are obtained without learning, the system can be realised very easily.