Study and Analysis of Thermal Imaging Sensors for Object Detection

International Journal of Electronics and Communication Engineering

© 2023 by SSRG - IJECE Journal

Volume 10 Issue 5

Year of Publication : 2023

Authors : B. Shubha, V. Veena Devi Shastrimath

10.14445/23488549/IJECE-V10I5P104

How to Cite?

B. Shubha, V. Veena Devi Shastrimath, "Study and Analysis of Thermal Imaging Sensors for Object Detection," SSRG International Journal of Electronics and Communication Engineering, vol. 10,  no. 5, pp. 38-48, 2023. Crossref, https://doi.org/10.14445/23488549/IJECE-V10I5P104

Abstract:

Low-resolution thermal imaging sensors are extensively used for applications where human privacy needs to be protected, and continuous monitoring is essential. Thermal sensors are increasingly used in indoor environmental applications like health monitoring, security, and innovative housing. Such sensors provide low-resolution images. However, these low-resolution images are sufficient to detect the objects. This paper studies and analyses two thermal imaging sensors by considering their characteristics, detection capability, and performance. It recommends the type of sensor to be used in specific applications. The received data from the sensor is processed, and image enhancement is carried out using the interpolation technique. Human detection is achieved by removing the background noise and converting the Image to binary. The experiments were conducted in the laboratory using Grid-EYE and MLX90640 thermopile sensors to detect the human in real-time. The processing of the sensor data is implemented using Raspberry Pi.

Keywords:

Filtering, Interpolation, Raspberry Pi, Thermopile image sensor, Thermal image.

References:

[1] Seigo Kanazawa et al., “A Fuzzy Automated Object Classification by Infrared Laser Camera,” Proceedings of SPIE - The International Society for Optical Engineering, Security and Sensing, vol, 8058, pp. 805815-1-9, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[2] B. Shubha, V. Veena Devi Shastrimath, and L. V. Prabhu, “Parameter Analysis of Pyroelectric and Thermopile Detectors,” International Conference for Emerging Technology (INCET), pp. 1-7, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Claudia Chiţu et al., “Wireless System for Occupancy Modeling and Prediction in Smart Buildings,” 25th Mediterranean Conference on Control and Automation (MED), pp. 1094-1099, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Panasonic Industry, Infrared Array Sensor Grid-EYE. [Online]. Available: https://industrial.panasonic.com
[5] Melexis, MLX90640 32x24 IR Array Datasheet, 2018. [Online]. Available:https://www.melexis.com
[6] Akshaya D. Shetty et al., “Detection and Tracking of a Human Using the Infrared Thermopile Array Sensor - “Grid-EYE”,” International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), pp. 1490-1495, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Dongning Qu, Bo Yang, and Nanhao Gu, “Indoor Multiple Human Targets Localization and Tracking Using Thermopile Sensor,” Infrared Physics & Technology, vol. 97, pp. 349–359, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Abdallah Naser, Ahmad Lotfi, and Joni Zhong, “Towards Human Distance Estimation Using a Thermal Sensor Array,” Neural Computing and Applications, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Hessam Mohammadmoradi et al., “Measuring People-Flow Through Doorways Using Easy-to-Install IR Array Sensors,” 13th International Conference on Distributed Computing in Sensor Systems (DCOSS), pp. 35-43, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Congcong Ma et al., “Work Engagement Recognition in Smart Office,” Procedia Computer Science, vol. 200, pp. 451-460, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Cristian Perra et al., “Monitoring Indoor People Presence in Buildings Using Low-Cost Infrared Sensor Array in Doorways,” Sensors, vol. 21, no. 12, pp. 4062, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Mika Maaspuro, “Infrared Occupancy Detection Technologies in Building Automation-A Review,” ARPN Journal of Engineering and Applied Sciences, vol. 13, no. 19, pp. 8055–8068, 2018.
[Google Scholar] [Publisher Link]
[13] Veena Chidurala, and Xinrong Li, “Detection of Moving Objects Using Thermal Imaging Sensors for Occupancy Estimation,” Internet of Things, vol. 17, pp. 100487, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Veena Chidurala, Xinrong Li, “Occupancy Estimation Using Thermal Imaging Sensors and Machine Learning Algorithms,” In IEEE Sensors Journal, vol. 21, no. 6, pp. 8627-8638, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] V. Diana Earshia, and M. Sumathi, “A Comprehensive Study of 1D and 2D Image Interpolation Techniques,” International Conference on Communications and Cyber Physical Engineering (ICCCE), pp. 383-391, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Richard Alan Peters II, Image Processing Lecture Notes: Resizing Images, 2015. [Online]. Available: https://ia902707.us.archive.org/23/items/Lectures_on_Image_Processing/EECE_4353_15_Resampling.pdf
[17] B. Shubha, and V. Veena Devi Shastrimath, “Real-Time Occupancy Detection System Using Low-Resolution Thermopile Array Sensor for Indoor Environment,” IEEE Access, vol. 10, pp. 130981-130995, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Liu Liu, Yue Chen, and Bo Yan, “An Efficient Classification-Based Image Interpolation Algorithm,” 4th International Congress on Image and Signal Processing, pp. 1063-1066, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Rafael C. Gonzalez, Richard E. Woods, Digital Image Processing, 3rd edition, Prentice Hall, 2008. [Online]. Available: https://www.academia.edu/67778643/Digital_Image_Processing_Third_Edition
[20] Gaussian Filtering. [Online]. Available: https://homepages.inf.ed.ac.uk/rbf/HIPR2/gsmooth.htm
[21] Gaussian Filter. [Online]. Available: https://link.springer.com/content/pdf/10.1007/978-1-84800-297-5_5.pdf
[22] Anna A. Trofimova et al., “Indoor Human Detection Based on Thermal Array Sensor Data and Adaptive Background Estimation,” Journal of Computer and Communications, vol. 5, no. 4, pp.16-28, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Payel Roy et al., “Adaptive Thresholding: A Comparative Study," 2014 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), pp. 1182-1186, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Sheikh Ferdoush, and Xinrong Li, “Wireless Sensor Network System Design Using Raspberry Pi and Arduino for Environmental Monitoring Applications,” Procedia Computer Science, vol. 34, pp. 103-110, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Raspberry Pi 4 Tech Specs. [Online]. Available: https://www.raspberrypi.com/products/raspberry-pi-4-model-/specifications
[26] Priyadharshini S., S.Natarajan, and S.Kavitha, “USB Device Driver Development of Image Processing Using Raspberry Pi 4 via Thingspeak,” SSRG International Journal of Electronics and Communication Engineering, vol. 8, no. 6, pp. 1-3, 2021.
[CrossRef] [Publisher Link]
[27] Chandan A D et al., “Survey Paper on Vehicle Security Using Facial Recognition & Password,” SSRG International Journal of Electronics and Communication Engineering, vol. 9, no. 6, pp. 5-9, 2022.
[CrossRef] [Publisher Link]
[28] V. Teju, and D. Bhavana, “An Efficient Object Tracking in Thermal Imaging Using Optimal Kalman Filter,” International Journal of Engineering Trends and Technology, vol. 69, no. 12, pp. 197-202, 2021.
[CrossRef] [Publisher Link]
[29] Sudhir Dagar, and Geeta Nijhawan, “Area Efficient Moving Object Detection using Spatial and Temporal Method in FPGA,” International Journal of Engineering Trends and Technology, vol. 70, no. 9, pp. 138-147, 2022.
[CrossRef] [[Publisher Link]
[30] V.Vivek et al., “Development of Abandoned Object Detection Based on Region of Interest Method,” International Journal of Computer and Organization Trends, vol. 8, no. 6, pp. 1-6, 2018.
[Publisher Link]
[31] D. J. Samatha Naidu, and B. Lakshmi Devi, “Vehicle Speed Tracking Detection Using Gaussian Mixture Models,” SSRG International Journal of Mobile Computing and Application, vol. 9, no. 3, pp. 1-4, 2022.
[CrossRef] [Publisher Link]
[32] Esmaeil Mirmahdi, and Omid Ghorbani Shirazi, “Installation of Suitable Sensors for Object Detection and Height Control on Combine Harvester,” SSRG International Journal of Mechanical Engineering, vol. 8, no. 5, pp. 12-19, 2021.
[CrossRef] [Google Scholar] [Publisher Link]