Image Segmentation with Automatically Balanced Constraints

Graph cut based interactive segmentation is useful to extract objects from images. Color and gradient constraints are two terms appearing in most of energy functions of related methods. In order to balance the two constraints, state-of-the-art methods adopt a pre-given fixed weight. However, different images and even different parts in a single image have different demands for proportion of the two constraints. This paper proposes a graph cut based segmentation method which is capable of intelligently balancing the two constraints on the fly. Particularly, it analyzes the demand of each pixel for color and gradient constraints and arranges a weight at the pixel to balance the two, automatically. Results show that the proposed method obtains better results than traditional ones.