Thermal Imaging Analysis of Potentially Harmful Subject for Night Vision System

• Main Authors: Noor Amira Syuhada, Mahamad Salleh, Kamarul Hawari, Ghazali
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/5955/1/Thermal_imaging_analysis_of_potentially_harmful_subject_for_night_vision.pdf; http://umpir.ump.edu.my/id/eprint/5955/; http://worldconferences.net/proceedings/aics2013/toc/papers_aics2013/A068%20-%20NOOR%20AMIRA%20SYUHADA%20M.%20SALLEH%20-%20Thermal%20Imaging%20Analysis%20of%20Potentially%20Harmful%20Subject%20for%20Night%20Vision%20System.pdf

Thermal imaging is now widely used in important and high risk field. With the good performance to detect the object in poor lighting condition, thermal imaging is used as the advanced technology in the critical surveillance activity. Surveillance system become a critical issue when it comes to a critical area cover by the responsible party such as military , police and others security organization. Besides, the computing technology contributes the easiness of implementing digital image processing in many applications. This can greatly improve the effectiveness of the surveillance activity done at the critical surveillance area. Hence, this present paper proposed few techniques on image processing to enhance the surveillance efficiency based on the thermal image dataset. The selection of the correct technique is followed the specification, process and output from this thermal surveillance system. The method of frame difference is used since the detection is on the moving subject. Image processing is fully used to fulfill the identification of the subject. By using the edge characteristic of the subject, the identification and image analysis use the boundary information. The feature of subject detected is analysed to improve the identification of the existence of the potentially harmful subject. The algorithm developed able to identify the subject come across the critical surveillance area. Analysis of the study is using a dataset of night surveillance activities which include the possibilities of harmful and harmless subject. Finally, the system will automatically differentiate and identify the subject and indicate the existing subject is harmful or harmless subject. The experimental results show the detection with better accuracy.