Gestalt saliency: Salient region detection based on Gestalt principles

Abstract

Salient region detection is of great significance in computer vision such as object recognition, image segmentation and image retrieval. However, low-level saliency has certain limitations due to lack of object level information. In this paper, we propose a saliency detection method based on Gestalt principles in which we introduce mid-level Gestalt concepts for low-level saliency. We propose an algorithm based on Gestalt principles of similarity & anomaly to select and suppress the similar background regions, using variance of clusters of image regions. Moreover, we propose two smoothing procedures based on Gestalt principles of similarity & proximity to group near and similar regions and therefore uniformly highlight the salient object. Experimental results on public data set show that our method performs well compared with state-of-the-art approaches.