English handwriting image edge detection based on fuzzy logic

Xueying Wang; Hongwei Liu; Yuanshen Wang

doi:10.1117/12.2684395

1 August 2023 English handwriting image edge detection based on fuzzy logic

Xueying Wang, Hongwei Liu, Yuanshen Wang

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127540C (2023) https://doi.org/10.1117/12.2684395
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

This paper mainly applies fuzzy logic to the edge detection of handwritten images in English. Image edge detection is an important part of image processing. Through image edge detection, the amount of data can be greatly reduced, and the information that can be considered irrelevant can be eliminated, and the important structural attributes of the image are retained. It uses six traditional operators to detect the edge of English handwritten images: canny, log, sobel, sprewitt, zerocross, and roberts. By comparing the edge detection results of the two kinds of experiments, we can find that the canny operator has the best edge detection effect among the traditional operators. In the fuzzy logic experiment, with the growth of 𝐒_𝐱 and 𝐒_𝐲, the edge detection effect gradually weakened. In this paper, the experiment with 𝐒_𝐱 = 𝟎. 𝟎𝟓 and 𝐒_𝐲 = 𝟎. 𝟎𝟓 has the best edge detection results. In conclusion, the edge detection effect of English handwritten images based on fuzzy logic is better than that of English handwritten images based on traditional methods.

Citation Download Citation

Xueying Wang, Hongwei Liu, and Yuanshen Wang "English handwriting image edge detection based on fuzzy logic", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127540C (1 August 2023); https://doi.org/10.1117/12.2684395

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KEYWORDS

Edge detection

Fuzzy logic

Image processing

Detection and tracking algorithms

Binary data

Image segmentation

Machine learning

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