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Optimization of Sequential Filters
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-9091-4724
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
1995 (English)In: Proceedings of the SSAB Symposium on Image Analysis: Linköping, Sweden, 1995, 87-90 p.Conference paper, Published paper (Refereed)
Abstract [en]

A recursive method for separation of spherically separable quadrature filters into simple kernels with mainly one dimensional extent has been worked out. The resulting filter responses are mapped to a non biased tensor representation where the local tensor constitutes a robust estimate of both the shape and the orientation (velocity) of the neighbourhood. The performance of this General Sequential Filter concept has exceeded the authors most optimistic expectations. A qualitative evaluation results in no detectable loss in accuracy when compared to conventional FIR (Finite Impulse Response) filters but the computation is performed 20-30 times faster. The magnitude of the attained speed-up implies that complex spatio-temporal analysis can be performed using standard hardware, such as a powerful workstation, in close to real time. Due to the soft implementation of the convolver and the tree structure of the sequential filtering approach the processing is simple to optimize for most standard hardware. The method used in the examples was implemented in AVS (Application Visualization System) using modules written in C.

Place, publisher, year, edition, pages
1995. 87-90 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-21748OAI: oai:DiVA.org:liu-21748DiVA: diva2:273873
Available from: 2009-10-25 Created: 2009-10-05 Last updated: 2013-08-28

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Knutsson, HansAndersson, Mats

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