A Configurable Architecture for the Generalized Hough Transform Applied to the Analysis of Huge Aerial Images and to Traffic Sign Detection

被引：0

作者：

Kiefer, Gundolf ^{[1
]}

Vahl, Matthias ^{[2
]}

Sarcher, Julian ^{[1
]}

Schaeferling, Michael ^{[1
]}

机构：

[1] Univ Appl Sci Augsburg, Dept Comp Sci, Hsch 1, D-86161 Augsburg, Germany

[2] Fraunhofer Inst Graph Datenverarbeitung IGD, Dept Maritime Graph, Joachim Jungius Str 11, D-18059 Rostock, Germany

来源：

2016 INTERNATIONAL CONFERENCE ON RECONFIGURABLE COMPUTING AND FPGAS (RECONFIG16) | 2016年

关键词：

Generalized Hough Transform; FPGA; SoC; Object Recognition; Computer Vision; Aerial Images; Traffic Sign Detection;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Object recognition in huge image data sets or in live camera images at interactive frame rates is a very demanding task, especially within embedded systems. The recognition task includes the localization of a reference object and its rotation and scaling in a search image. The Generalized Hough Transform (GHT) is known as a powerful and robust technique to support this task by transforming the search image into a 4D parameter space. However, the GHT itself is very complex and demanding towards computational power and memory consumption. This paper presents a novel hardware architecture to perform a complete 4D GHT at interactive frame rates in an FPGA. The architecture is configurable in order to allow a trade-off between performance, accuracy and hardware usage. The proposed architecture has been implemented in a low-cost Zynq-7000 FPGA and successfully evaluated in two practical applications, namely groyne detection in aerial images and traffic sign detection.

引用

页数：7