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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 4, ISSUE 9, SEPTEMBER 2015

Raspberry Pi Based Human Face Detection

Swathi .V, Steven Fernandes

DOI: 10.17148/IJARCCE.2015.4942

Abstract: Face detection is concerned with finding whether or not there are any faces in a given image and, if present, returns the image location and content of each face. Most face detection algorithms are designed in the software domain and have a high detection rate, but they often require several seconds to detect faces in a single image, a processing speed that is insufficient for real-time applications. This paper describes a simple and easy hardware implementation of face detection system using Raspberry Pi, which itself is a minicomputer of a credit card size and is of a very low price. The system is programmed using Python programming language. Both real time face detection and face detection from specific images, i.e. Object Recognition, is carried out and the proposed system is tested across various standard face databases, with and without noise and blurring effects. Efficiency of the system is analyzed by calculating the Face detection rate for each of the database. The results reveal that the proposed system can be used for face detection even from poor quality images and shows excellent performance efficiency.



Keywords: Face detection, Raspberry Pi, Histogram Equalization, Python.

How to Cite:

[1] Swathi .V, Steven Fernandes, “Raspberry Pi Based Human Face Detection,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2015.4942