The magnetic moment of magnetically labeled cells, microbubbles or microspheres is an important optimization parameter for many targeting, delivery or separation applications. The quantification of this property is often difficult, since it depends not only on the type of incorporated nanoparticle, but also on the intake capabilities, surface properties and internal distribution. We describe a method to determine the magnetic moment of those carriers using a microscopic set-up and an image processing algorithm. In contrast to other works, we measure the diversion of superparamagnetic nanoparticles in a static fluid. The set-up is optimized to achieve a homogeneous movement of the magnetic carriers inside the magnetic field. The evaluation is automated with a customized algorithm, utilizing a set of basic algorithms, including blob recognition, feature-based shape recognition and a graph algorithm. We present example measurements for the characteristic properties of different types of carriers in combination with different types of nanoparticles. Those properties include velocity in the magnetic field as well as the magnetic moment. The investigated carriers are adherent and suspension cells, while the used nanoparticles have different sizes and coatings to obtain varying behavior of the carriers.