Proceedings of the 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)

An Optimal Fuzzy Logic Algorithm for Edge Detection of Stone Inscriptions

Authors
Jie Song, Jie Wang, Shanshan Li
Corresponding Author
Jie Song
Available Online March 2018.
DOI
https://doi.org/10.2991/mecae-18.2018.6How to use a DOI?
Keywords
Image Processing, Edge detection, Fuzzy Logic, Stone inscriptions.
Abstract
The identification of stone inscriptions is of great significance to the study of Chinese characters and the exploration of ancient history. Characters are the symbol of civilization. The identification and analysis of the stone inscriptions can determine the age when they belong, and can help to study archeology. In this paper, an optimal fuzzy logic algorithm is proposed for edge detection of stone characters. Using the adaptive median filter to denoise the stone inscriptions; using three linear filters for gradient analysis; reasonable set of fuzzy rules and fuzzy sets. During image preprocessing, three linear filters are used: the Sobel operator, which is used to estimate the derivative of the horizontal and vertical directions, the low-pass filter and the high-pass filter. The setting of parameter N enhances the adaptive ability of this algorithm and can be applied to different types of image detection. The algorithm is compared with the existing algorithms (Sobel, canny), and better results are achieved.
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Proceedings
2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
Part of series
Advances in Engineering Research
Publication Date
March 2018
ISBN
978-94-6252-493-4
DOI
https://doi.org/10.2991/mecae-18.2018.6How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Jie Song
AU  - Jie Wang
AU  - Shanshan Li
PY  - 2018/03
DA  - 2018/03
TI  - An Optimal Fuzzy Logic Algorithm for Edge Detection of Stone Inscriptions
BT  - 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/mecae-18.2018.6
DO  - https://doi.org/10.2991/mecae-18.2018.6
ID  - Song2018/03
ER  -