This paper presents a multiresolution system for volumetric texture analysis. The originality of this system partially originates from its use of combinations of perceptual texture features that correspond to adjectives commonly used by humans to describe textures. To approximate these features, we use a combination of different families of texture analysis methods rather than a single texture analysis model. This choice is necessary to obtain a good perceptual feature approximation and allows our system to be robust and generic. Moreover, by using our human-understandable features (HUF), it is convenient for a user to manipulate and select the features that are, according to the user, relevant for a given application. Two experiments are presented: the first experiment demonstrates the strong correspondence between our features and a human's description of textures, and the second demonstrates the performance of our proposed method. Finally, the proposed HUF are integrated into an interactive segmen-tation system and are compared to previously proposed descriptors through analysis of several segmentation results of 3D ultrasound images.