The present paper discusses the essential tenets of the method whose purpose is to enable effective search of images of given rock in multimedia databases. The search is based exclusively on an image request, to which the system’s response is a set of images presenting visually similar rocks. The images that constitute the basis of the discussed research had been registered with an optical microscope. The collection of images that were used in the process of performing measurements encompassed 5700 digital images presenting 19 rock types. The proposed method is based on the application of image analysis and artificial intelligence concepts. The very process of inference, in turn, makes use of the methods of data classification and grouping. In the paper, the authors demonstrate that these may turn out to be effective mathematical methods, successfully applied to the problem of image search, performed with imagings presenting rock textures. The discussed system concept, based on a feature space defined by the authors, successfully matches up images with the reference standard. The effectiveness rate of that process is very high (very often, it is 100 %). Failed classifications concern only the images which differ visually—in a considerable way—from the rest of the images within a given group. The proposed system concept is to facilitate the decision-making process involved in determining the similarity of investigated objects. In the opinion of the authors, it meets the requirements—and, as such, can be applied to the problem of searching for images in databases, searching discs in order to find images of given rocks and automatic information gain on the basis of video sequences, e.g., in order to find frames presenting particular rock structures.