AbstractBased on Gestalt principles, in this paper we model features for measuring the degree of similarity between combinations of image components, and grouping areas in trademark images are recognized. This investigation can be used for content‐based image retrieval from the perspective of mirroring human perception of images. The features of proximity, shape similarity, closure, and good continuation are extracted from every combination of two components in an image. After that, based on the decision results, a grouping pattern for the query is fixed. Besides changing combinations of features, the proposed method can output multiple grouping patterns. In the experiments, we evaluated the proposed method on 74 test images, comparing outputs produced by the proposed method and grouping patterns for the test images obtained from questionnaires filled out by 104 participants. © 2009 Wiley Periodicals, Inc. Electron Comm Jpn, 92(10): 49–60, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10007