Improved Thermographic Object Detection relying-on Image Processing and Sensorial Development of Quantum IR Photodetectors

Abstract

The manuscript is devoted to improve of the thermographic object detection. This research work complies two phases. The first phase of this framework focuses on the enhancement of quantum IR photodetectors (QIRPs) performance based on studying the responsivity (R) and its dependence on QIRPs parameters. The semiconductor-based QRIPs include quantum (well QWIPs, wire QRIPs, and dot QDIPs) photodetectors. Moreover, the study is directed to the most sensitive device among these three quantum types. While the second phase of the study presents robust object detection in IR images by employing multistage efficient image processing techniques. Firstly, we enhance the quality of the images to simplify the process of object extraction. This enhancement, preprocessing, relies mainly on denoising and histogram quantization. Secondly, the segmentation phase is employed to extract the object under interest.The segmentation is implemented based on fuzzy c-mean clustering.