FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR

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Abstract

This paper presents an efficient approach to corner detection in images using a spiral addressing scheme in conjunction with simulated, biological involuntary eye movements. As part of this approach, a combined gradient detection and smoothing operation is used to quickly obtain a feature representation that can be used with a standard ‘cornerness’ measure. A computationally efficient use of the spiral address scheme to apply further processing operations such as non-maximum suppression is demonstrated. Comparative evaluation of three corner detection methods is presented and results demonstrate significantly faster processing times than other well-known corner detection methods.
Original languageEnglish
Number of pages5
Publication statusAccepted/In press - 20 Jun 2018
EventInternational Conference on Artificial Intelligence and Pattern Recognition - North China University of Technology (NCUT), Beijing, China
Duration: 18 Aug 201820 Aug 2018
http://www.aipr.net

Conference

ConferenceInternational Conference on Artificial Intelligence and Pattern Recognition
Abbreviated titleAIPR 2018
CountryChina
City Beijing
Period18/08/1820/08/18
Internet address

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    Fegan, J., Coleman, S., Kerr, D., & Scotney, B. (Accepted/In press). FAST, BIOLOGICALLY INSPIRED CORNER DETECTION USING A SQUARE SPIRAL ADDRESS SCHEME AND ARTIFICIAL EYE TREMOR. Paper presented at International Conference on Artificial Intelligence and Pattern Recognition , Beijing, China.