Mining Frequent Spatial Patterns in Image Databases with 17D-SPA Representation

In this paper, we propose a new algorithm for mining frequent patterns in image databases. Our method mines patterns with more accuracy than a previously known algorithm and can be beneficial, where small differences in object locations can change the pattern. In this regard, we generate larger patterns from smaller ones and check whether the support for each candidate is less than a user-specified amount.