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10 October 2003 Dynamic detection model and its application for perimeter security, intruder detection, and automated target recognition
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Under unsteady weather conditions (gusty wind and partial cloudiness), the pixel intensities measured by infrared or optical imaging sensors may change considerably within even minutes. This makes a principal obstacle to automated target detection and recognition in real, outdoor settings. Currently existing automated recognition algorithms require strong similarity between the weather conditions of training and recognition. Empirical attempts to normalize image intensities do not lead to reliable detection in practice (e.g. for scenes with a complex relief). Also if the weather is relatively stable (weak wind, rare clouds), as short as 15-20 minutes delay between the training survey and the recognition survey may badly affect target recognition or detection, unless the targets are well separable from background. Thermal IR technologies based on invariants such as emissivity and thermal inertia are expensive and ineffective in making the recognition automated. Our approach to overcoming the problem is to take advantage of multitemporal prior surveying. It exploits the fact, that any new infrared or optical image of a scene can be accurately predicted based on sufficiently many scene images acquired previously. This removes the above severe constraints to variability of the weather conditions, whereas neither meteorological measurement nor radiometric calibration of the sensor are required. The present paper further generalizes the approach and addresses several points that are important for putting the ideas in practice. Two experimental examples: intruder detection and recognition of a suspicious target illustrate the potential of our method.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joseph Koltunov and Alexander Koltunov "Dynamic detection model and its application for perimeter security, intruder detection, and automated target recognition", Proc. SPIE 5074, Infrared Technology and Applications XXIX, (10 October 2003);


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