Abstract: An apparatus is provided for compensating for the effect of a moving door on a nearby ferromagnetic object detector. The ferromagnetic object detector is of a type to produce a main sensor signal indicative of the presence of a ferromagnetic object in the vicinity of the ferromagnetic object detector. Furthermore, the door is arranged relative to the ferromagnetic object detector such that movement of the door is liable to introduce an undesirable interference signal into the main sensor signal. The apparatus comprises an input (3) for receiving the main sensor signal and a door sensor signal that is responsive to an opening angle of the door. The apparatus also comprises an interference signal estimator (4) for estimating a door-related interference signal in dependence upon the door sensor signal and a model of interference for the door.

Abstract: An apparatus is provided for compensating for the effect of a stray ferromagnetic object moving past but not through a sensing region of a ferromagnetic object detector. The ferromagnetic object detector is of a type to produce a plurality of sensor signals, each sensor signal being influenced by the presence of a genuine ferromagnetic object moving through the sensing region but also liable to be influenced by the presence of the stray object. The apparatus comprises: an input for receiving the plurality of sensor signals and first means for analysing the received signals to determine whether there is a substantially same time-varying component present in each of the signals. The apparatus also comprises second means for determining whether the plurality of signals without the contribution of that time-varying component are each or collectively below a predetermined level of significance.

Abstract: A method of classifying an object, in particular of classifying a vehicle by evaluating the degree of correlation between an image data set corresponding to an image of at least part of the vehicle and each of a plurality of reference data sets each of which corresponds to a reference image of a vehicle comprises the steps of establishing the vehicle's aspect and selecting the plurality of reference data sets from a larger group of such data sets on the basis of the vehicle's aspect. By selecting from the larger group only those reference data sets which correspond to the vehicle's aspect, faster classification is achieved for a given level of processing resources. Alternatively, for a given processing or classification rate, the level of processing resources may be reduced compared to the prior art.