A hybrid system for embedded machine vision using FPGAs and neural networks

被引：2
|
作者：
Prieto, Miguel S. [1 ]
Allen, Alastair R. [1 ]
机构：
[1] Univ Aberdeen, Sch Engn & Phys Sci, Aberdeen AB24 3UE, Scotland
来源：
MACHINE VISION AND APPLICATIONS | 2009年 / 20卷 / 06期
关键词：
Embedded machine vision; FPGA; ANN; SOM; ROAD SIGN DETECTION; CLASSIFICATION;
D O I：
10.1007/s00138-008-0133-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a hybrid model for embedded machine vision combining programmable hardware for the image processing tasks and a digital hardware implementation of an artificial neural network for the pattern recognition and classification tasks. A number of possible architectural implementations are compared. A prototype development system of the hybrid model has been created, and hardware details and software tools are discussed. The applicability of the hybrid design is demonstrated with the development of a vision application: real-time detection and recognition of road signs.
引用
收藏
页码：379 / 394
页数：16
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