Abstract
This paper proposes an approach for automatic text extraction method using neural networks. Automatic text extraction is a crucial stage for multimedia data mining. We present an artificial neural network (ANNs)-based approach for text extraction in complex images, which uses a combined method of ANNs and non-negative matrix factorization (NMF)-based filtering. An automatically constructed ANN-based classifier can increase recall rates for complex images with small amount of user intervention. NMF-based filtering enhances the precision rate without affecting overall performance. As a result, a combination of two learning mechanism leads to not only robust but also efficient text extraction.
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