A novel method for image edge extraction based on the Hausdorff derivative

Lin Qiu, Ji Lin, Wen Chen, Fajie Wang and Qingsong Hua

Physica A: Statistical Mechanics and its Applications, 2020, vol. 540, issue C

Abstract: Image edge extraction based on the differential equations is an important branch of image processing. This paper makes the first attempt to employ the Hausdorff derivative gradient method (HDHM) to extract the image edge. In terms of the visual quality of details, contours, edge integrity, and continuity, the original images and noisy images were extracted by using an appropriate fractal dimension. Numerical results indicate that the HDGM outperforms the Sobel operator, Canny algorithm and traditional gradient method. Moreover, it can be confirmed that the proposed method with multiple values is effective for some images on which the gray value in different parts is quite different. This work extends the Hausdorff derivative to a new field and provides an effective methodology for image edge extraction.

Keywords: Image edge extraction; Hausdorff fractal distance; Hausdorff derivative; Gradient method (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:540:y:2020:i:c:s0378437119317674

DOI: 10.1016/j.physa.2019.123137

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