An incremental learning strategy for handwritten character recognition is proposed in this paper. The strategy is online and fast, in the sense that any new character class can be instantly learned by the system. The proposed strategy aims at overcoming the problem of lack of training data when introducing a new character class. Synthetic handwritten characters generation is used for this purpo...

Because of the characteristics high redundancy, parallelism and nonlinearity in handwritten character recognition model, convolutional neural networks (CNNs) are becoming first choice to solve these complex problems. The complexity, types characters, similarity dataset, optimizers all have a great impact on network resulting low accuracy, loss, other In view existence problems, an improved LeNe...

This paper presents a features extraction module for isolated handwritten Arabic characters. The collected core features are based on pixels orientations according to Freeman chain code. The input to this module is Arabic character (in its basic-shapes i.e. without diacritics). The features extractor module, fed with a skeleton of an isolated character basic-shape, yields global and local featu...

Pre-classification can effectively improve the performance of handwritten Chinese character recognition. This paper presents a method that uses four corner feature for pre-classification of handwritten Chinese characters. Considering writing variations, we define a set of basic stroke structures and match them with the structures in four corner regions of character image. The matching result wi...

In this paper, the generalized learning vector quantization (GLVQ) algorithm is applied to design a handwritten Chinese character recognition system. The system proposed herein consists of two modules, feature transformation and recognizer. The feature transformation module is designed to extract discriminative features to enhance the recognition performance. The initial feature transformation ...

Creating document image datasets with ground-truths of regions, text lines and characters is a prerequisite for document analysis research. However, ground-truthing large datasets is not only laborious and time consuming but also prone to errors due to the difficulty of character segmentation and the large variability of character shape, size and position. This paper describes an effective reco...