Abstract
The traditional Harris corner detection algorithm is sensitive to noise, and Corner is prone to drift at different image resolution. Combined with the multi-scale features of wavelet transform, propose a corner detection algorithm based on the wavelet transform. The algorithm maintains the advantages of Harris corner detection algorithm in image scaling, rotation or gray scale change, improves its disadvantage of scale invariance, and has strong anti-noise and real-time performance. It has good anti-noise and real-time performance.
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Acknowledgements
Project found: (1) Young teachers development and support program of Anhui Technical College of Mechanical and Electrical Engineering (project number: 2015yjzr028); (2) Anhui Quality Engineering Project “Industrial Robot Virtual Simulation Experimental Teaching Center” (project number:2016xnzx007); (3) nhui Province Quality Engineering Project “Exploration and Practice of Innovative and Entrepreneurial Talents Training Mechanism for Applied Electronic Technology Specialty in Higher Vocational Colleges” (project number:2016jyxm0196); (4) Anhui Quality Engineering Project (MOOC) “Off-line Programming of Industrial Robots” (project number:2017 mooc091).
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Sun, Q. (2020). An Improved Harris Corner Detection Algorithm. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_14
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DOI: https://doi.org/10.1007/978-981-13-6504-1_14
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