基于嵌入式的近红外人脸识别系统设计

设计并实现了一套基于达芬奇平台OMAP3530的近红外人脸识别系统。本系统采用850nm的LED灯提供主动的近红外光源,在OMAP3530和EPM570处理器的协同作用下,实现了可见光图像与近红外图像的实时采集与处理。软件设计基于Codec Engine架构,ARM端负责图像的采集、识别结果的显示和数据库的管理;DSP端专注于人脸识别算法。通过图像采集、人脸检测、特征提取和特征匹配4个步骤实现人脸识别。本系统充分利用了OMAP3530丰富的接口和强大的图像处理能力,并且经过了C与汇编语言的优化。当环境光强发生变化时,系统仍能获得较高的识别精度和较好的实时性。

Design of Near-Infrared Face Recognition System Based on Embedded Technique

A near-infrared face recognition system using DaVinci technology (OMAP3530) and embedded technique is proposed. The system uses 850 nm wavelength LEDs to provide proactive near-infrared light. Coordinating by OMAP3530 and EPM570 processors, it achieves visible and near-infrared images in real-time. The software design is based on the Codec Engine framework. Within the proposed system, ARM is responsible for image acquisition, user interface and database management, while DSP focuses on the core algorithms of image evaluation, face localization, feature extraction and matching. The system takes full advantage of the rich interface and powerful ima ge processing capability of OMAP3530 and is optimized by the C and assembly languages. Even when the light intensity changes, the system can still obtain accurate and fast recognition results.