Handwriting Identification By Using Neuro Fuzzy Methods Based On Features Extraction

Abstract

Handwriting recognition system is a system to recognize one's writing through paper. This technology identifies a unique and fixed piece of writing like human handwriting. The character pattern recognition on human handwriting words utilizes image processing and analysis of characters which will play an important role in the handwriting recognition process. The system will search for characters and then insert into a pre-prepared reference database through the training process. In this research it will be made recognition system by utilizing human handwriting. In the initial process it will be data retrieval in the form of words with the size of 500 x 500 pixels and segmentation of each character of 24 x 20 pixels which will then perform feature extraction using Principal Component Analysis (PCA) to determine the characteristics of the characters. After that the results will be done by recognizing Using Adaptive Neuro Fuzzy Inference System to measure the similarity between training data and test data. From the trial application using Neuro Fuzzy classification it obtained accurate recognition accuracy of 65.37%, in the scenario with 3 training data. While 7 training data, it obtained accurate recognition accuracy of 80%.

Authors and Affiliations

Aeri Rachmad

Keywords

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  • EP ID EP392063
  • DOI 10.9790/9622-0708048084.
  • Views 100
  • Downloads 0

How To Cite

Aeri Rachmad (2017). Handwriting Identification By Using Neuro Fuzzy Methods Based On Features Extraction. International Journal of engineering Research and Applications, 7(8), 80-84. https://europub.co.uk/articles/-A-392063