Simplified Quadtree Image Segmentation for Image Annotation

This paper introduces a Quadtree image segmentation technique to be used for image annotation. The proposed method is able to efficiently divide the image in homogeneous segments by merging adjacent regions using border and color information. Our method is highly efficient and provides segmentations of acceptable performance; the segments generated with the proposed technique can be used for automatic image annotation and related tasks (e.g., object recognition). A benefit of our proposal is that it allows us finishing the segmentation at any time by controlling the desired level of the detail for the segmentation; hence, the method is suitable for time restricted scenarios. We compare the performance of an image annotation technique trained on hand labeled images and tested in images segmented with different segmentation algorithms. We found that the best results were obtained when the annotation method was tested in images segmented with the quadtree formulation. Our results give evidence of the efficiency and effectiveness of the proposed method.