Automatic Presence System with Face Recognition Based Smartphone Camera Using the Haar Cascade Method

EasyChair Preprint 10527

Abstract

The technology developed in this century has made it possible to create an automatic presence system. The focus of this research is on the system's presence using face recognition by applying the Haar cascade method. The Haar Cascade Classifier, also known as haar-like features, utilizes rectangular features (square function). By utilizing the DroidCam application on a smartphone to obtain the IP camera feed, the system can be programmed to detect presence using the smartphone's camera. The program is created using IDLE, a Python-based language. Tests have been conducted, including face registration, automatic detection of unknown objects, and system database verification. The Haar cascade algorithm is known for its speed in capturing objects, resulting in real-time processing. However, there are several factors that can affect its performance, such as distance and lighting conditions. The ideal distance for presence detection is within the range of 20cm to 40cm and light level within range of 100 to 20.

Keyphrases: Droidcam, Haar Cascade, Python, face recognition, idle

@booklet{EasyChair:10527,
  author    = {Hendrico Ajey and Rina Mardiati and Lia Kamelia},
  title     = {Automatic Presence System with Face Recognition Based Smartphone Camera Using the Haar Cascade Method},
  howpublished = {EasyChair Preprint 10527},
  year      = {EasyChair, 2023}}