基于树莓派的手掌静脉平台及模式增强模型设计

Liukui Chen, Xiaoxing Wang, H. Jiang, Li Tang, Zuojin Li, Yao Du
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引用次数: 0

摘要

近年来,随着生物识别技术的飞速发展,静脉识别正在慢慢融入我们的生活。目前,手静脉和指静脉的相关应用较多。手掌静脉位于皮肤深处,会干扰手掌指纹,这增加了获取手掌指纹的难度,导致应用相对较少。本文在研究手掌静脉图像采集的基础上,设计了一套辅助采集设备,在舒适的体感环境下完成对手掌静脉图像的采集。该设备以树莓派为模型核心,辅以发光光源、光学传感器、控制芯片、小显示屏等配件,可以完成静脉图像的采集。并通过受限对比度直方图均衡化、高斯去噪、gabor滤波等针对树莓派掌纹优化的算法,增强掌纹线条,提高图像质量。该模型将多个模块集成到一个模具中,大大减小了模型的体积,提高了整体采集过程的速度,具有良好的应用价值。
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Design of Palm Vein Platform and Pattern Enhancement Model Based on Raspberry Pi
In recent years, with the rapid development of biometrics technology, vein recognition is slowly integrating into our lives. At present, there are many related applications of hand veins and finger veins. The palm veins are deep under the skin and interfere with palm prints, which increases the difficulty of obtaining them, resulting in relatively few applications. Based on the research of palm vein image acquisition, this paper designs a set of auxiliary acquisition equipment to complete the acquisition of vein images under a comfortable somatosensory. The device takes the Raspberry Pi as the core of the model, supplemented by accessories such as luminous light source, optical sensor, control chip and small display, which can complete the collection of vein images. And through the algorithm of restricted contrast histogram equalization, Gaussian denoising, gabor filtering and other algorithms optimized for palm veins in the Raspberry Pi, the palm vein lines are enhanced to improve the image quality. The model integrates multiple modules into one mold, greatly reduces the volume of the model, improves the speed of the overall collection process, and has good application value.
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