EmoSecure: Enhancing Smart Home Security With FisherFace Emotion Recognition and Biometric Access Control

The focus of smart homes is more inclined towards providing security and comfort to residents rather than treating energy as the foremost concern. This paper proposes a novel technique combining the FisherFace-based emotion recognition and the biometric security using the iris features for smart homes. The proposed emotion-based smart home system can refresh the user's mood by detecting a real-time facial expression and adjusting the house environment - lighting, air-conditioning, and music system, accordingly. The unique features are the pattern of ridges in the iris and the pattern made by nerves on the sclera. The Canny edge detection is used to find the ridges along with pseudo coloring processing. The proposed iris bio-metrics security rests on the unique features obtained from the ridges of the iris. Resident authentication is provided through iris recognition, following which emotion recognition occurs. This model presents iris recognition through modified linear binary patterns and Daugman sheet conversion. The face extraction from a live video occurs using the Haar xml files, which retrieve the frontal face. Face emotions are then detected through edge extraction by applying Sobel filters and a combination of several steps - composite mask and eigenvectors followed by FisherFace recognition. A combination of these techniques produces a higher accuracy and recognition rate. The proposed system has shown a promising accuracy of 95.25% for iris recognition and 93.93% for emotion detection.