Stavros J. Perantonis and Paulo J.G. Lisboa,
Translation, Rotation, and Scale Invariant Pattern
Recognition by Higher-Order Neural Networks and Moment Classifiers,
IEEE Transactions on Neural Networks,
3, 2, pp. 241-251, March 1992.
Stavros J. Perantonis and Paulo J.G. Lisboa,
Translation, Rotation, and Scale Invariant Pattern
Recognition by Higher-Order Neural Networks and Moment Classifiers,
IEEE Transactions on Neural Networks,
3, 2, pp. 241-251, March 1992.The classification and recognition of two-dimensional patterns independently of their position, orientation, and size by using high-order networks are discussed. A method is introduced for reducing and controlling the number of weights of a third-order network used for invariant pattern recognition. The method leads to economical networks that exhibit high recognition rates for translated, rotated, and scaled, as well as locally distorted, patterns. The performance of these networks at recognizing typed and handwritten numerals independently of their position, size and orientation is compared with and found superior to the performance of a layered feedforward network to which image features extracted by the method of moments are presented as input.