Review of Feature Extraction Techniques for Character Recognition

This paper presents a comprehensive review of the feature extraction techniques for character recognition (CR) which will be helpful for the new researchers to understand the insight into the developments of the current research in the field of CR. Feature extraction plays a major role in the performance of the CR. The characteristics of the feature extraction techniques have to be independent of the scalable font characteristics such as type, size, style, tilt, rotation and should be able to describe the complex, distorted, broken characters effectively. A feature vector should be simple, reliable, complete, and compact to recognize any input character with high accuracy similar to human perception. A lot of research has been done on feature extraction techniques for optical CR for the past few decades. Most of the existing CR methods from the literature will work successfully for one or two fonts and they have used the combination of existing features to improve the accuracy. Therefore, we feel there is still scope to work on feature extraction techniques for the recognition of multilingual characters.