Content based image retrieval (CBIR), a technique which tries to find a set of images similar to a given example. Low level descriptors can be used to represent and index images. The main problem of CBIR is the gap between these descriptors and abstract concepts. The proposal present in this paper resembles the search process within a set of objects. First, objects can be found in a collection by looking general features and discarding those objects that do not fit into these features to reduce the search space. Next, another more specific feature can help to find these objects in the reduced search space. This work proposes the arrangement of low level descriptors into a hierarchy. This arrangement has to be done considering the detail of information that descriptor gives. Finally, descriptors on each level of the hierarchy are used to index images in the search space and a filter to reduce it has to be executed. This process is repeated until the low level of the hierarchy is reached. Experiments demonstrate the effectiveness of the proposed approach compared with the traditional ones and reveal it as a good option to implement CBIR systems.