Gradient-threshold edge detection based on the human visual system

Fuzheng Yang; Yilin Chang; Shuai Wan

doi:10.1117/1.1850747

Gradient-threshold edge detection based on the human visual system

Fuzheng Yang, Yilin Chang, Shuai Wan

Xidian University

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

We present an improved method that is suitable for gradient-threshold edge detectors. The method takes into account the basic characteristics of the human visual system and masks the gradient image with the luminance and the activity of local image before edge labeling. An implementation of this method on a Canny detector is described as an example. The results show that the edge images obtained by our algorithm are more consistent with the perceptive edge images.

Original language	English
Pages (from-to)	1-2
Number of pages	2
Journal	Optical Engineering
Volume	44
Issue number	2
DOIs	https://doi.org/10.1117/1.1850747
State	Published - Feb 2005
Externally published	Yes

Keywords

Edge detection
Human visual system
Perceptive edge

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10.1117/1.1850747

Cite this

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title = "Gradient-threshold edge detection based on the human visual system",

abstract = "We present an improved method that is suitable for gradient-threshold edge detectors. The method takes into account the basic characteristics of the human visual system and masks the gradient image with the luminance and the activity of local image before edge labeling. An implementation of this method on a Canny detector is described as an example. The results show that the edge images obtained by our algorithm are more consistent with the perceptive edge images.",

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AU - Chang, Yilin

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AB - We present an improved method that is suitable for gradient-threshold edge detectors. The method takes into account the basic characteristics of the human visual system and masks the gradient image with the luminance and the activity of local image before edge labeling. An implementation of this method on a Canny detector is described as an example. The results show that the edge images obtained by our algorithm are more consistent with the perceptive edge images.

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KW - Human visual system

KW - Perceptive edge

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M3 - 文章

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Gradient-threshold edge detection based on the human visual system

Abstract

Keywords

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