Dynamic Fuzzy Background Removal for Indoor Human Target Perception Based on Thermopile Array Sensor

With the ageing of population, timely assistance for the living-alone elderly is becoming a worldwide problem. The precondition of assistance is to correctly and timely perceive human behavior. The thermopile array sensor is one of the most promising perception sensors, similar to a low-resolution infrared imaging camera. Besides humans, computers and many other objects indoors emit infrared radiation and hence can be captured by the infrared thermopile array sensor at the same time. The background of the infrared image of sensor is complex and dynamically changing, and we should remove the dynamic background, i.e. to remove non-human thermal disturbances first. Based on a thermopile array sensor MLX90640, with an array output of
$24\times32$
pixels, this paper proposes a dynamic fuzzy spatiotemporal background removal (DFBR) for human activity perception. Each pixel of the sensor’s output has its own dynamic parameters, background temperature (
${{BT}}$
) and temperature threshold (
${{TT}}$
), which are used to dynamically determine this pixel to be removed or not. A fuzzy background membership function is proposed to update each pixel’s
${{TT}}$
and
${{BT}}$
based on background change and temperature value below the human body. The pixel whose temperature is lower than the sum of its
${{TT}}$
and
${{BT}}$
would be removed. The corrosion is used to make the infrared image clear after background removal. Moreover, a foreground complement is proposed to complement the misremoval due to the thermal disturbance. The experimental results have shown that the DFBR can remove the background of low-resolution infrared image online dynamically and correctly.