A Fuzzy Based Feature Extraction Approach for Handwritten Characters
نویسندگان
چکیده
This paper describes a technique that can be used to generate fuzzy rules to extract the features of handwritten characters. The feature extraction is a complicated problem as different people write the same character in different ways. The development of a technique that can generate the description of handwritten characters is still a challenge for the handwritten recognition systems. The fuzzy logic offers a good opportunity to build a rule-based feature extraction technique for handwritten characters with low computational cost.
منابع مشابه
Neural Network Based Recognition System Integrating Feature Extraction and Classification for English Handwritten
Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...
متن کاملWavelet Packet Transform and Neuro-fuzzy Approach to Handwritten Character Recognition
This paper presents a novel method for automatic handwritten character recognition by combining wavelet packet transform with neurofuzzy approach. The time-frequency localization and compression capability of wavelet packet transform using best-basis algorithm is used for feature extraction, enhancing the accuracy of recognition at pixel level. The best-basis algorithm automatically adapts the ...
متن کاملA Zoning based Feature Extraction method for Recognition of Handwritten Assamese Characters
This paper introduces a novel feature extraction approach for handwritten Assamese character recognition. The performance of an optical character recognition system highly depends on the extracted feature set. Hence, feature extraction plays a significant role in achieving high recognition accuracy. Also, not all the features of an image are useful for classification and therefore feature extra...
متن کاملOptimizing Feature Selection for Recognizing Handwritten Arabic Characters
Recognition of characters greatly depends upon the features used. Several features of the handwritten Arabic characters are selected and discussed. An off-line recognition system based on the selected features was built. The system was trained and tested with realistic samples of handwritten Arabic characters. Evaluation of the importance and accuracy of the selected features is made. The recog...
متن کاملImplementation of Feed-forward Neural Network Models for Pattern Classification Using Transformation Based Feature Extraction Methods
Automatic recognition of handwritten Hindi characters is a difficult and one of the most interesting research areas of pattern recognition field. A lot of work has been done in this area till date; still it is a subject of active research. Hindi characters are cursive in nature and thus characters may be written in various cursive ways. Characters also show a lot of similar features such as hea...
متن کامل