A robust, low-cost approach to Face Detection and Face Recognition

TL;DR

This paper presents a low-cost, robust face detection and recognition system that works with low-quality images from inexpensive devices, using Discrete Wavelet Transform and color space properties for accurate frontal face extraction.

Contribution

The paper introduces a novel face recognition approach combining DWT and color space analysis suitable for low-quality images from low-cost devices.

Findings

Achieved high recognition accuracy with low-cost camera images.

Effective frontal face detection using L*a*b* color space properties.

Comparison of DWT decomposition levels optimized recognition performance.

Abstract

In the domain of Biometrics, recognition systems based on iris, fingerprint or palm print scans etc. are often considered more dependable due to extremely low variance in the properties of these entities with respect to time. However, over the last decade data processing capability of computers has increased manifold, which has made real-time video content analysis possible. This shows that the need of the hour is a robust and highly automated Face Detection and Recognition algorithm with credible accuracy rate. The proposed Face Detection and Recognition system using Discrete Wavelet Transform (DWT) accepts face frames as input from a database containing images from low cost devices such as VGA cameras, webcams or even CCTV's, where image quality is inferior. Face region is then detected using properties of L*a*b* color space and only Frontal Face is extracted such that all additional background is eliminated. Further, this extracted image is converted to grayscale and its dimensions are resized to 128 x 128 pixels. DWT is then applied to entire image to obtain the coefficients. Recognition is carried out by comparison of the DWT coefficients belonging to the test image with those of the registered reference image. On comparison, Euclidean distance classifier is deployed to validate the test image from the database. Accuracy for various levels of DWT Decomposition is obtained and hence, compared.