Adaptive Fractional Differentiation Harris Corner Detection Algorithm for Vision Measurement of Surface Roughness

Joint Authors

Tang, Rui-Yin
Zeng, Zhou-Mo

Source

Advances in Mathematical Physics

Issue

Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2014-04-17

Country of Publication

Egypt

No. of Pages

6

Main Subjects

Physics

Abstract EN

The Harris algorithm via fractional order derivative (the adaptive fractional differentiation Harris corner detection algorithm), which adaptively adjusts the fractal dimension parameter, has been investigated for an analysis of image processing relevant to surface roughness by vision measurements.

The comparative experiments indicate that the algorithm allows the edge information in the high frequency areas to be enhanced, thus overcoming shortcomings.

The algorithm permits real-time measurements of surface roughness to be performed with high precision, superior to the conventional Harris algorithm.

American Psychological Association (APA)

Tang, Rui-Yin& Zeng, Zhou-Mo. 2014. Adaptive Fractional Differentiation Harris Corner Detection Algorithm for Vision Measurement of Surface Roughness. Advances in Mathematical Physics،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-476136

Modern Language Association (MLA)

Tang, Rui-Yin& Zeng, Zhou-Mo. Adaptive Fractional Differentiation Harris Corner Detection Algorithm for Vision Measurement of Surface Roughness. Advances in Mathematical Physics No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-476136

American Medical Association (AMA)

Tang, Rui-Yin& Zeng, Zhou-Mo. Adaptive Fractional Differentiation Harris Corner Detection Algorithm for Vision Measurement of Surface Roughness. Advances in Mathematical Physics. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-476136

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-476136