Abstract
We examined the possibility of applying cellular automata to solve the problem on recognition of text characters. For this purpose, we introduced the notion of competing cellular automata and developed algorithms of their functioning and interaction. In order to implement the proposed algorithms, we created modeling software. It allowed us to evaluate effectiveness of the cellular-automaton algorithms to conduct experiments on text character recognition using the English alphabet and to demonstrate a number of advantages in comparison with other methods. We investigated a description of the solution to the problem on selecting the structural attributes in the images of text characters, which directly affect the quality of recognition. In the present work, it is proposed to use a set of cellular automata constructed on the diagrams of states of Moore and Mealy machines for each type of cellular automata, to determine the end points, junctions and cycles in characters. We considered operation of the modeling program. The advantages of the given technology are the simplicity of rules of interaction, easy parallelization of the process of recognition, the possibility of recognition of distorted and partially overlapping characters. We compared performance quality and efficiency of the commercially available system ABBYY FineReader, which has demonstrated high performance indicators of the developed recognition technology
Highlights
We examined the quality of text recognition
Oper- Error aton percenttime, s age Results of the studies conducted have shown the effectiveness of the proposed method of text character recognition based on competing cellular automata
The developed information technology allowed us to achieve a high quality of recognition and provided us with tools for further research
Summary
The systems of character recognition, which are part of the tasks on pattern recognition, are used today in many areas of human activity: from document management systems and all the way up to the modern-day robotics [1,2,3,4,5]. In paper [6], author demonstrated indisputable advantages of applying cellular automata (CA) for the problems where there is a need for parallelization of computations that enables simple implementation of complex algorithms for pattern processing, which does not require significant computing resources Despite these advantages, cellular automata have not been often employed in the tasks on recognition. There is a real way to apply a new, proposed by authors of [11,12,13,14], type of CA directly to the process of character recognition Such approach is based on movable CA, which should implement all their states on the appropriate text symbol. This block executes image segmentation algorithms; the image is split into lines and letters, which are basically the objects of recognition
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