In this paper, a novel approach based on the wavelet orthonormal decomposition is presented to extract features in pattern recognition. The proposed approach first reduces the dimensionality of a two-dimensional pattern, and thereafter performs wavelet transform on the derived one-dimensional pattern to generate a set of wavelet transform subpatterns, namely, several uncorrelated functions. Based on these functions, new features are readily computed to represent the original two-dimensional pattern. As an application, experiments were conducted using a set of printed characters with varying orientations and fonts. The results obtained from these experiments have consistently shown that the proposed feature vectors can yield an excellent classification rate in pattern recognition.

Based on wavelets, a theoretical method has been developed to process multi-gray level documents. In this method, two-dimensional multiresolution analysis, a wavelet decomposition algorithm, and compactly supported orthonormal wavelets are used to transform a document image into sub-images. According to these sub-images, the reference lines of a multi-gray level document can be extracted, and knowledge about the geometric structure of the document can be acquired. Particularly, this approach is more efficient to process form documents with gray level background. Experiments indicate that this new method can be applied to process documents with promising results.

In this paper, we present a novel approach to optical character recognition that utilizes ring-projection-wavelet-fractal-signatures. In particular, the proposed approach reduces the dimensionality of a two-dimensional pattern by way of a ring-projection method, and thereafter, performs Daubechies' wavelet transform on the derived one-dimensional pattern to generate a set of wavelet sub-patterns, namely, curves that are non-self intersecting. Further from the resulting non-self intersecting curves, the divider dimensions are readily computed. These divider dimensions constitute a new characteristic vector for the original two-dimensional pattern, defined over the curves' fractal dimensions.