Proceedings of WRFER International Conference, 24 th June, 2018, New Delhi, India 5 EFFICIENT HUMAN IDENTIFICATION THROUGH FACE DETECTION USING RASPBERRY PI BASED ON PYTHON-OPENCV 1 LOCHAN BASYAL, 2 BISHAL KARKI, 3 GAURAV ADHIKARI, 4 JAGDEEP SINGH 1,2,3 B.Tech. Students, Amritsar College of Engineering and Technology, Amritsar, India 4 Assistant Professor, Amritsar College of Engineering and Technology, Amritsar, India 1,4 Department of Electronics and Communication Engineering, Amritsar College of Engineering and Technology, Amritsar, India 2,3 Department of Computer Science Engineering, Amritsar College of Engineering and Technology, Amritsar, India E-mail: 1 bashyallochan@gmail.com Abstract - Human Identification can be performed through various technique like as fingerprint, palm detection, iris detection as well as face detection. This paper focus on implementation of face detection system for human identification based on open source computer vision library (OpenCV) with python. The model of face recognition has been performed on both laptop and raspberry pi whereas for an implementation of this project on laptop, SQLite studio has been used as a database and for raspberry PI PHPmyadmin has been used. In this paper the concept of detection has been established by writing different code for dataset generator, Trainer and detector. Finally the information that will be displayed along with detected photo has been stored on database. This concept has a higher scope on security and surveillance projects and various automation operation. Keywords - Face Detection, PHPmyadmin, PI Camera, Raspberry PI, SQLite Studio. I. INTRODUCTION The Concept of image processing through python OpenCV platform has been used for human identification through face detection. Human Identification means to recognize a particular people through his unique structure like fingerprint, palm, iris and face detection. This paper is based on the implementation of face detection system with the use of database. The testing of this technique has been proceed through laptop as well as raspberry PI devices. SQLite studio is used as a database for laptop and similarly PHPmyadmin for Raspberry PI, through this a user data has been stored in a particular sequence and can be manipulated with Detection Window where a current image of user has been displayed. This mechanism is based on three steps, for the first we need to take dataset of each person about 20 samples where an algorithm of face detection face.xml file is used and is based on OpenCV. The second step of human identification is trainer, which means we need to train our system and is converted that dataset into its corresponding .YML file format. This YML file has been used on detector script and is detected the respective face of user in real time when we run this detector file. Through this detector window we can see real time picture along with corresponding user information which has been linked with database and for an unknown person the system said an unauthorized person. This concept is highly applicable on security and surveillance Projects where we can manufactured an embedded system based on face detection and is used on door look mechanism. II. RELATED WORKS Patel and shah introduced [1] a survey on facial feature extraction techniques for automatic face annotation. Automatic face annotation is playing vital role in multimedia information. Automatic face annotation is method to identify human faces from image and assign appropriate human name. Face detection and face recognition are essential tasks in face annotation. An author also discuss the phases of the automatic face annotation and surveyed various techniques of facial feature extraction. Patoliya and Desai developed [2] proposed Face Detection based ATM Security System using Embedded Linux Platform. The system is implemented on the credit card size Raspberry Pi board with extended capability of open source Computer Vision (OpenCV) software which is used for Image processing operation. This technique is also based on OTP (one time password) for establishing a high security for ATM. In an unauthorized condition ATM door has been locked and it’s only when the OTP password is entered my watchman. Heshmat et al. [3] introduced Face Identification System in Video. An author proposed CIE-Luv color space, facial feature extraction and variance estimation. It can be applied in face recognition systems such as video surveillance, human computer interfaces, image database management and smart home applications. The experimental results demonstrate the effectiveness of this system and its ability to recognize a variety of different faces in spite of different pose, expression, zooming and illumination conditions. Setyadi et al. [4] presented Human Character Recognition Application Based on Facial Feature Using Face Detection. This System can detect the