基于FPGA的汽车盗窃实时检测系统的设计与实现

A. Ahilan, Esther Annlin, Kala James
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引用次数: 14

摘要

人脸检测是一种确定人脸图像位置和大小的技术。它检测面部特征,而忽略其他任何东西,如建筑物、树木和身体。人脸检测算法侧重于检测正面人脸,而较新的算法试图解决更普遍和更困难的多视图人脸检测问题。本文提出了一种基于Haar特征的Viola Jones算法的人脸检测系统的硬件结构。该算法已应用于汽车盗窃实时检测中。采用Verilog HDL语言设计了人脸检测体系结构,并在Xilinx Virtex-5 ML505 FPGA上实现。对其性能进行了测量,并与等效的软件实现进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and implementation of real time car theft detection in FPGA
Face detection is a technique that determines the locations and sizes of human face images. It detects facial features and ignores anything else, such as buildings, trees and bodies. Face-detection algorithms focused on the detection of frontal human faces, whereas newer algorithms attempt to solve the more general and difficult problem of multi-view face detection. This paper presents a hardware architecture for face detection system based on Viola Jones algorithm using Haar features. The proposed algorithm is used in real time car theft detection. The architecture for face detection is designed using Verilog HDL and implemented in Xilinx Virtex-5 ML505 FPGA. Its performance has been measured and compared with an equivalent software implementation.
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