摘要：Superpixel segmentation is the oversegmentation of an image into a set of homogeneous regions. Superpixel has many specific properties and has been commonly used as supporting regions for primitives to reduce computations in various computer vision tasks. One property of superpixels is compactness, which is preferred in some applications. In this paper, we give an review on image superpixel segmentation algorithms proposed in recent years. Superpixel segmentation approaches are classified based on the compactness constraint and their main idea are introduced. We also compare these algorithms in visual and evaluate them with five common measurements.

摘要：Superpixels generation is becoming increasingly popular as a preprocessing in many computer vision applications. A superpixel is an image patch which has uniform pixels intensity and is aligned with intensity edges. Superpixels provide a convenient primitive from which local image features can be computed. So far, there are many methods to generate superpixels. Several main superpixels generation algorithms are summarized in this paper and the advantages and disadvantages of them are analyzed simply. In the end, some applications of superpixels are listed.