Edge Detection of Degraded Stone Inscription Kannada Characters Using Fuzzy Logic Algorithm

K, Rajithkumar B; Mohana, H. S.; Uday, J; Batra, Uma

doi:10.1007/978-981-10-3223-3_2

Cited by 2 publications

(1 citation statement)

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“…Edge detection has been applied to various fields. The cell images and Kannada stone inscriptions are blurred by calculating the X-axis and Y-axis gradients, and the gradient images are added as input to the fuzzy inference system [1,2]. The proposed method employs a 3x3 mask guided by fuzzy rule set.…”

Section: Introductionmentioning

confidence: 99%

An Optimal Fuzzy Logic Algorithm for Edge Detection of Stone Inscriptions

Song¹,

Wang²,

Li³

2018

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

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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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Section: Introductionmentioning

confidence: 99%