HMAX Image Processing Pipeline with Coupled Oscillator Acceleration

Abstract

In this paper we report on the performance of a coupled oscillator based implementation of the HMAX image-processing pipeline. Within this pipeline we have used coupled oscillator arrays to replace traditional Boolean logic with a Degree-of-Match (DoM) function that measures the L2 distance squared between two vectors in an n-dimensional space. We show that this operation can be used in three stages of the pipeline: 1) as a substitute for convolution in filtering operations, 2) as a computational kernel for pattern matching, and 3) as a distance function in a nearest neighbor classification algorithm. In this study, we have modeled the performance of the latter two and report our recognition results over a test set from the Neo Vision2 image database.

Original document

The different versions of the original document can be found in:

• https://zenodo.org/record/1280246 under the license https://creativecommons.org/share-your-work/public-domain/cc0/

• https://zenodo.org/record/1280246/files/article.pdf

• http://xplorestaging.ieee.org/ielx7/6973465/6986048/06986101.pdf?arnumber=6986101,

http://dx.doi.org/10.1109/sips.2014.6986101 under the license cc0

• https://dblp.uni-trier.de/db/conf/sips/sips2014.html#JenningsBGCFCL14,

https://academic.microsoft.com/#/detail/2003232723