Image segmentation is one of the most basic tasks in computer vision and remains an initial
step of many applications. In this paper, we focus on interactive image segmentation (IIS) …

As fuzzy c-means clustering (FCM) algorithm is sensitive to noise, local spatial information is
often introduced to an objective function to improve the robustness of the FCM algorithm for …

A great number of improved fuzzy c-means (FCM) clustering algorithms have been widely
used for grayscale and color image segmentation. However, most of them are time …

Clustering image pixels is an important image segmentation technique. While a large
amount of clustering algorithms have been published and some of them generate …

Clustering algorithms by minimizing an objective function share a clear drawback of having
to set the number of clusters manually. Although density peak clustering is able to find the …

Semantic segmentation with dense pixel-wise annotation has achieved excellent
performance thanks to deep learning. However, the generalization of semantic …

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By
considering the original pairwise distance in the contextual space, we develop a feature …

Morphological reconstruction (MR) is often employed by seeded image segmentation
algorithms such as watershed transform and power watershed, as it is able to filter out seeds …

The fuzzy c-partition entropy has been widely adopted as a global optimization technique for
finding the optimal thresholds when performing multilevel gray image segmentation …

This article presents a multi-phase image segmentation methodology based on fuzzy
superpixel decomposition, aggregation and merging. First, a collection of layers of dense …