Table of Contents

1. Introduction
2. Principles of Thermal Imaging
3. Video Analysis in Thermal Cameras
4. Numerical Analysis Parameters
5. Savgood Company Solutions
6. References

Introduction

Thermal cameras have become essential tools in fields such as security, firefighting, and industrial inspection. These devices measure the infrared radiation emitted by objects to produce images and analyze video footage, capturing temperature variations that are invisible to the naked eye.

Principles of Thermal Imaging

Thermal imaging cameras rely on the principle that all objects emit infrared radiation as a function of their temperature. The camera's sensor, usually an uncooled microbolometer, detects this radiation and converts it into an electronic signal. This signal is processed to form an image displaying temperature variations.

Video Analysis in Thermal Cameras

Thermal cameras use advanced algorithms to analyze video footage. These algorithms assess pixel-level temperature differences, detect motion, and recognize patterns. Video analytics in thermal imaging include activity detection, boundary intrusion detection, and object classification based on temperature signatures.

Numerical Analysis Parameters

• Resolution: Typically ranges from 160x120 pixels to 640x480 pixels. High-resolution thermal cameras can provide more detailed visualizations.
• Temperature Sensitivity (NETD): Noise Equivalent Temperature Difference, usually measured in millikelvins (mK). A lower NETD value indicates higher sensitivity to temperature differences, with values often ranging from 30 mK to 100 mK.
• Frame Rate: Standard thermal cameras operate at 9 Hz or 30 Hz, which affects the fluidity of the video.
• Field of View (FOV): Expressed in degrees, it typically ranges from 20° to 60°, influencing the area the camera can observe.

Savgood Company Solutions

Savgood Technology provides cutting-edge solutions for thermal imaging video analysis. Their products integrate with thermal cameras to enhance performance and deliver precise analytics. Key features include:

• Advanced Motion Detection: Algorithms capable of differentiating between human and non-human movements based on thermal profiles.
• Real-time Temperature Monitoring: Continuous assessment and alerts for abnormal temperature readings, essential for critical infrastructure monitoring.
• Integration with AI Systems: AI-powered analytics for anomaly detection and predictive maintenance in industrial settings.

References

1. Infrared Training Center (ITC). Thermal Imaging Guidebook for Building and Renewable Energy Applications. Fluke Corporation, 2011.
2. Budzier, Helge, and Gerhard Gerlach. Thermal Infrared Sensors: Theory, Optimisation and Practice. John Wiley & Sons, 2011.
3. Savgood Technology Co., Ltd. Thermal Imaging Solutions. Savgood, 2023.
4. Bharat, Mishra. Principles and Applications of Thermal Imaging. Springer, 2019.