盲人静态手势和人脸识别系统

Saransh Sharma, Samyak Jain, Khushboo
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引用次数: 25

摘要

本文提出了一种能够帮助盲人的识别系统。本文实现了手势识别系统和人脸识别系统,利用它们可以完成各种任务。动态图像是从动态视频中提取的,并根据一定的算法进行处理。在手势系统中,在YCbCr颜色空间中进行皮肤颜色检测,提取手指、手指夹角等不同特征,利用手的特征点来发现手凸缺陷。根据手势识别,可以执行各种任务,如打开风扇或灯。而在人脸识别中,Haar级联分类器和LBPH识别器分别用于人脸检测和识别。在OpenCV的帮助下,本研究得以实现。使用该系统可以检测和识别各种手势和人脸。手势识别的准确率达到95.2%,面部识别的准确率达到92%。
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A Static Hand Gesture and Face Recognition System for Blind People
This paper presents a recognition system, which can be helpful for a blind person. Hand gesture recognition system and face recognition system has been implemented in this paper using which various tasks can be performed. Dynamic images are being taken from a dynamic video and is being processed according to certain algorithms. In the Hand gesture system Skin color detection has been done in YCbCr color space and to discover hand convex defect character point of hand is used where different features like fingertips, angle between fingers are being extracted. According to gesture Recognized, various tasks can be performed like turning on the fan or lights. While in face recognition, Haar Cascade Classifiers and LBPH recognizer are being used for face detection and recognition respectively. With the help of OpenCV, The research has been implemented. Various hand gestures and human faces have been detected and identified using this system. The hand gesture was recognized with an accuracy of 95.2% was achieved and facial recognition was done with an accuracy of 92%.
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