Table of Contents Author Guidelines Submit a Manuscript
Advances in Mathematical Physics
Volume 2014 (2014), Article ID 494237, 6 pages
Research Article

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

1State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, China
2College of Electrical Engineering, Hebei United University, 46 Xinhua Road, Tangshan 063009, China

Received 13 March 2014; Accepted 19 March 2014; Published 17 April 2014

Academic Editor: Xiao-Jun Yang

Copyright © 2014 Rui-Yin Tang and Zhou-Mo Zeng. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.