手势识别系统设计与开发分析研究 计算机专业VIP专享VIP免费

摘要随着计算机技术与信息处理技术迅速发展，智能化电子设备逐渐进入到日常的生产和生活中，与此同时，人们对电子设备操作过程的便捷化也提出了新的要求，这也促使计算机进行图像处理的技术也得到了发展。近些年兴起的模式识别技术为操作便捷化提供了新的研究方向和发展平台，其中通过对手势的识别来向电子产品进行命令操作逐渐成为一项新的关键技术。目前，手势识别技术已经逐步应用在AR和汽车辅助驾驶等方面，同时，在人机交互过程中应用手势识别技术还可以提高体验感。所以，研究开发手势识别系统具有一定的学术意义和经济价值。这项技术涉及了包含静态图片识别与分析、视频图像处理及计算机视觉等多方面内容。本文介绍了开发手势识别系统的背景及意义，分析了过程中涉及到的必要步骤及算法。本系统基于C++环境使用OpenCV开源计算机视觉库进行手势识别。本系统通过计算机本地单目摄像头录入手势，分别对动态和静态手势进行识别，并实时显示不同手势所表示的结果。总体上可分为图像采集、图像预处理，特征提取及识别四个模块，具体包括非线性中值滤波、形态学膨胀滤波、HOG特征和SVM分类等步骤。目前系统开发完成，实验结果基本可以实现手势的识别，并显示出结果。关键词：图像处理；手势识别；OpenCV；计算机视觉ABSTRACTWiththerapiddevelopmentofcomputertechnologyandinformationprocessingtechnology,intelligentelectronicequipmenthasgraduallyenteredintodailyproductionandlife.Atthesametime,peoplehaveputforwardnewrequirementsfortheconvenienceofelectronicequipmentoperationprocess,whichalsopromotesthedevelopmentofcomputerimageprocessingtechnology.Theemergingpatternrecognitiontechnologyinrecentyearsprovidesanewresearchdirectionanddevelopmentplatformfortheconvenienceofoperation,amongwhichthecommandoperationofelectronicproductsthroughgesturerecognitionhasgraduallybecomeanewkeytechnology.Atpresent,gesturerecognitiontechnologyhasbeengraduallyappliedinAR,automobileassisteddrivingandotheraspects.Meanwhile,theapplicationofgesturerecognitiontechnologyinhuman-computerinteractioncanalsoimprovethesenseofexperience.Therefore,theresearchanddevelopmentofgesturerecognitionsystemhascertainacademicsignificanceandeconomicvalue.Thetechnologyinvolvesstaticimagerecognitionandanalysis,videoimageprocessingandcomputervision.Thispaperintroducesthebackgroundandsignificanceofdevelopinggesturerecognitionsystem,andanalyzesthenecessarystepsandalgorithmsinvolvedintheprocess.ThissystemusesOpenCVopensourcecomputervisionlibraryforgesturerecognitionbasedonC++environment.Inthissystem,gesturesarerecordedbycomputerlocalmonocularcamera,andthedynamicandstaticgesturesarerecognizedrespectively,andtheresultsofdifferentgesturesaredisplayedinrealtime.Ingeneral,itcanbedividedintofourmodules:imageacquisition,imagepreprocessing,featureextractionandrecognition,includingnonlinearmedianfiltering,morphologicalexpansionfiltering,HOGfeatureandSVMclassification.Atpresent,thesystemhasbeendeveloped,andtheexperimentalresultscanbasicallyrealizegesturerecognitionanddisplaytheresults.Keywords:Imageprocessing;Gesturerecognition;OpenCV;Computervision目录1绪论..............................................................................................................................................................11.1课题背景及意义...............................................................................................................................11.2手势识别的发展现状.......................................................................................................................11.3本文主要内容.........................