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2 August 1999 Real-time target detection technique for metal detector arrays: an image processing approach
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A vehicle-width array of metal detectors is one of the sensor systems used in most present day vehicle-mounted mine detectors. Data furnished by such a metal detector array consist of an output from each sensor channel as a function of time which is usually converted to a function of position. In multisensor systems where target-level data fusion is used, there is a need for techniques to process such data in order to detect and locate targets in realtime as the array scans the ground surface. One conventional way of processing such data is to apply a thresholding algorithm to data from each sensor channel separately and infer the presence of a target under a given coil or a number of coils. Such as approach could be very limited and cumbersome particularly when one has to consider large arrays with complex interaction between sensor and targets that produce a response in a number of sensor channels simultaneously. In this paper we model the data from the detector array as a scrolling image and develop a target detection and location scheme based on image processing concepts. Modifications of multiresolution and template-matching algorithms of 'peak' detection are developed using domain -specific knowledge of metal detector arrays. The resulting technique, which also uses dynamic thresholding to allow realtime operation, is illustrated using measured data from a 24-element, 3-meter wide metal detector array.
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Kevin L. Russell, Yogadhish Das, John E. McFee, and Robert Chesney "Real-time target detection technique for metal detector arrays: an image processing approach", Proc. SPIE 3710, Detection and Remediation Technologies for Mines and Minelike Targets IV, (2 August 1999);

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