Translation-invariant pattern recognition based on Synfire chains

1999 ◽  
Vol 80 (6) ◽  
pp. 433-447 ◽  
Author(s):  
Hans-Martin R. Arnoldi ◽  
Karl-Hans Englmeier ◽  
Wilfried Brauer
Keyword(s):  
Pattern Recognition ◽  
Translation Invariant ◽  
Synfire Chains

Rotation, scale, and translation invariant pattern recognition using feature extraction

1997 ◽  
Author(s):  
Donald Prevost ◽  
Michel Doucet ◽  
Alain Bergeron ◽  
Luc Veilleux ◽  
Paul C. Chevrette ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Feature Extraction ◽  
Translation Invariant

scholarly journals Pattern recognition on FPGA for aerospace applications

2021 ◽  
Vol 10 (12) ◽  
pp. e83101219181
Author(s):  
Francisco de Assis Tavares Ferreira da Silva ◽  
Magno Prudêncio de Almeida Filho ◽  
Antonio Macilio Pereira de Lucena ◽  
Alexandre Guirland Nowosad
Keyword(s):  
Mathematical Modeling ◽  
Pattern Recognition ◽  
Mathematical Morphology ◽  
Template Matching ◽  
Active Sensors ◽  
Translation Invariant ◽  
Time Pattern ◽  
Aerospace Applications ◽  
Field Programmable ◽  
Hardware Description

This paper presents a low power near real-time pattern recognition technique based on Mathematical Morphology-MM implemented on FPGA (Field Programmable Gate Array). The key to the success of this approach concerns the advantages of machine learning paradigm applied to the translation invariant template-matching operators from MM. The paper shows that compositions of simple elementary operators from Mathematical Morphology based on ELUTs (Elementary Look-Up Tables) are very suitable to embed in FPGA hardware. The paper also shows the development techniques regarding all mathematical modeling for computer simulation and system generating models applied for hardware implementation using FPGA chip. In general, image processing on FPGAs requires low-level description of desired operations through Hardware Description Language-HDL, which uses high complexity to describe image operations at pixel level. However, this work presents a reconfiguring pattern recognition device implemented directly in FPGA from mathematical modeling simulation under Matlab/Simulink/System Generator environment. This strategy has reduced the hardware development complexity. The device will be useful mainly when applied on remote sensing tasks for aerospace missions using passive or active sensors.

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