Improved FAST Corner Detection Based on Harris Algorithm for Chinese Characters

Abstract:

According to the characteristics of Chinese characters image, we propose an improved corner detection method based on FAST algorithm and Harris algorithm to improve detection rate and shorten the running time for next feature extraction in this paper. The image of Chinese characters is detected for corners using FAST algorithm Firstly. Second, computing corner response function (CRF) of Harris algorithm, false corners are removed. The corners founded lastly are the endpoints of line segments, providing the length of line segments for shape feature extraction. The proposed method is compared with several corner detection methods over a number of images. Experimental results show that the proposed method shows better performance in terms of detection rate and running time.

• Periodical: Advanced Materials Research (Volumes 850-851)
• Pages: 767-770
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.850-851.767
• Online since: December 2013
• Authors: Na Yao, Tie Cheng Bai, Jie Chen
• Keywords: Chinese Characters, Corner Detection, FAST, Harris

References

[1] H. Moravec, Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover, Tech Report CMU-RI-TR-3 Carnegie-Mellon University, Robotics Institute. (1980).

[2] C. Harris and M. Stephens, A combined corner and edge detector, Proceedings of the 4th Alvey Vision Conference. (1988).

DOI: 10.5244/c.2.23

[3] Alison Noble, Descriptions of Image Surfaces, PhD thesis, Department of Engineering Science, Oxford University 1989, p.45.

[4] C. Schmid, R. Mohrand and C. Bauckhage, Evaluation of Interest Point Detectors, Int. Journal of Computer Vision, 37(2), 151-172, (2000).

[5] J. Shi and C. Tomasi, Good Features to Track, 9th IEEE Conference on Computer Vision and Pattern Recognition. Springer. June (1994).

DOI: 10.1109/cvpr.1994.323794

[6] S. M. Smith and J. M. Brady, SUSAN - a new approach to low level image processing, International Journal of Computer Vision, 1997, 23 (1): 45–78.

[7] X. C. He and N. H. C. Yung, Curvature Scale Space Corner Detector with Adaptive Threshold and Dynamic Region of Support, Proceedings of the 17th International Conference on Pattern Recognition, 2: 791-794, August (2004).

DOI: 10.1109/icpr.2004.1334377

[8] X. C. He and N. H. C. Yung, Corner Detector based on Global and Local Curvature Properties, Optical Engineering, v. 47 n. 5, (2008).

[9] E. Rosten and T. Drummond, Fusing Points and Lines for High Performance Tracking, ICCV, (2005).

DOI: 10.1109/iccv.2005.104

[10] E. Rosten and T. Drummond, Machine Learning for High-speed Corner Detection, ECCV, (2006).

[11] E. Rosten, R. Porter and T. Drummond, Faster and Better: A machine Learning Approach to Corner Detection, " PAMI , (2008).