Pretouch sensors are capable to classify objects and estimate their position prior to touching and thus close the gap between vision- and contact-based sensing. This will be particularly useful for robotics applications not only just for manipulation of objects but also with respect to safety. As robots will more and more operate in “open environments” where there is little prior knowledge, it will be important to gather as much information on the environment as possible. However, although there are many measurement principles that might be applied, only a few can cope with the requirements, e.g., limitations with respect to spatial dimensions, weight, and power consumption. In this paper, we investigate a measurement system for two types of materials. Dielectric and ferromagnetic materials, which are common in many industrial applications, can be located and distinguished in the vicinity of a robot grasper. Inspired by magnetic field tomography, we use a permanent magnet and apply giant magnetic resistor sensors to measure the magnetic field deformation caused by ferromagnetic objects. Furthermore, we use an electrical capacitance tomography approach to measure the change of the electric field by dielectric objects. Based on the measurement results, we solve an inverse problem with respect to the object position and spatial permittivity distribution. We present experimental results for a prototype implementation and provide a description of the calibration method.