Research of Embedded Handwritten Alphanumeric Recognition System

DOI

10.2991/tlicsc-18.2018.58How to use a DOI?

Keywords

Handwritten Recognition; Alphanumeric String; Support Vector Machine; OpenCV.

Abstract

With the growing maturity of Internet of things, more and more hardware devices are developing towards intellectualization. Handwriting plays an increasingly important role in people's lives. However, due to the different writing habits, the character shape varies greatly. At present, the recognition effect scanners, mobile robots and other devices for handwritten characters is difficult to meet the needs. In this context, a handwritten alphanumeric string recognition system based on embedded development platform is developed. S3C2440 development board is selected as the hardware platform. OpenCV is used for image processing, and support vector machine (SVM) classification technology is used to realize the recognition of handwritten letters and digits. The system has the advantages of low power consumption and less memory consumption. It can be transplanted to various embedded devices to quickly identify handwritten alphanumeric strings and provide services for users in many fields such as mail sorting, report statistics and so on.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Kechao Wang
AU  - Mingshu Shang
AU  - Zhizheng Liu
AU  - Xiangmin Ren
PY  - 2018/12
DA  - 2018/12
TI  - Research of Embedded Handwritten Alphanumeric Recognition System
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 364
EP  - 368
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.58
DO  - 10.2991/tlicsc-18.2018.58
ID  - Wang2018/12
ER  -