Developments in the area of signature suppression make it progressively more difficult to recognize targets. The emphasis has been on the reduction of distinct features, like hot spots in the infrared band. Thus, to obtain a low false alarm rate, threat sensors have to utilize more information, i.e., spatial and spectral properties. The purpose of our work is to develop a general tool for camouflage assessment. The approach proposed applies texture descriptors to quantify the similarity between different parts of an image. In addition, other descriptors are used to distinguish man-made object characteristics. The selection of an appropriate set of features is discussed. The assumption is that an area containing observable targets has different statistics than other areas. Statistical properties along with detected target specific features have to be combined with methods used in data fusion. An experiment with a dataset of 44 reference images has been carried out, using a recently developed computer program called Terrtex. High correlation with perception experiments is achieved using only one or two texture features. The importance of a careful selection of background area size is finally discussed.