Handwritten letter recognition using LetNET

Dengyi Liu; Ao Wang; Yichen Wu

doi:10.1117/12.2641466

10 November 2022 Handwritten letter recognition using LetNET

Dengyi Liu, Ao Wang, Yichen Wu

Proceedings Volume 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022); 1234810 (2022) https://doi.org/10.1117/12.2641466
Event: 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 2022, Zhuhai, China

Abstract

Many people are accustomed to searching and managing information on electronic devices, but people only have handwritten documents in some cases. The handwritten character recognition techniques as useful tools for converting hand-wrote documents into machine-encoded text become more and more vital. There are many ways to implement handwritten character recognition, including line and word segmentation, semi-incremental, incremental, etc. However, recognition accuracy and training time are difficult to balance. This paper uses the convolutional neural network (CNN) method to train and fit the data. Firstly, preprocess the training data by resizing the images and abstracting letters from backgrounds. Then, the original dataset was set into the training set and fitting set for testing the model's effectiveness. Secondly, the dataset's CNN model was optimized, and eventually, the letNET module was decided to be used, an 8-layer deep convolutional neural network including the input layer. To test the practicability of this model in real life, a certain amount of handwritten words were set as a new testing dataset. The result shows the accuracy is felicitous even using self-wrote words. To verify the effectiveness of the proposed method, we compare our method with other state-of-the-art baselines, including random forest and support vector machines. The experiment result shows the letNET outperforms related benchmarks in handwritten characters recognition.

Citation Download Citation

Dengyi Liu, Ao Wang, and Yichen Wu "Handwritten letter recognition using LetNET", Proc. SPIE 12348, 2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2022), 1234810 (10 November 2022); https://doi.org/10.1117/12.2641466

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KEYWORDS

Optical character recognition

Data modeling

Convolution

Neural networks

Convolutional neural networks

Performance modeling

Precision measurement

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