Fast, Multi-Scale Image Processing on a Square Spiral Framework

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Abstract

Efficient processing of digital images is a key consideration in many machine vision tasks. Traditional image processing approaches often struggle to meet this demand, particularly at the initial low-level of processing image pixels. To overcome this, we propose a spiral based processing approach which takes inspiration from the asymmetric lattice of interlocking cells found in the human visual system. Here we demonstrate the efficiency of the proposed spiral approach for multi-scale feature extraction. This is complemented by a biologically inspired image acquisition process which is used to capture nine image frames at different spatial locations. The results demonstrate that the biologically inspired spiral approach offers a faster alternative to corresponding traditional image processing approaches
Original languageEnglish
Publication statusPublished - 18 Aug 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

Keywords

  • Fast Image Processing
  • Edge Detection
  • Multi-Scale Feature Extraction
  • Eye Tremor
  • Square Spiral Address Scheme

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  • Cite this

    Fegan, J., Kerr, D., Coleman, S., & Scotney, B. (2018). Fast, Multi-Scale Image Processing on a Square Spiral Framework. Paper presented at International Conference on Artificial Intelligence and Pattern Recognition , Beijing, China.