LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Fuzzy SLIC: Fuzzy Simple Linear Iterative Clustering

Photo by sarahdorweiler from unsplash

Most superpixel methods are sensitive to noise and cannot control the superpixel number precisely. To solve these problems, in this article, we propose a robust superpixel method called fuzzy simple… Click to show full abstract

Most superpixel methods are sensitive to noise and cannot control the superpixel number precisely. To solve these problems, in this article, we propose a robust superpixel method called fuzzy simple linear iterative clustering (Fuzzy SLIC), which adopts a local spatial fuzzy C-means clustering and dynamic fuzzy superpixels. We develop a fast and precise superpixel number control algorithm called onion peeling (OP) algorithm. Fuzzy SLIC is insensitive to most types of noise, including Gaussian, salt and pepper, and multiplicative noise. The OP algorithm can control the superpixel number accurately without reducing much computational efficiency. In the validation experiments, we tested the Fuzzy SLIC and OP algorithm and compared them with state-of-the-art methods on the BSD500 and Pascal VOC2007 benchmarks. The experiment results show that our methods outperform state-of-the-art techniques in both noise-free and noisy environments.

Keywords: linear iterative; iterative clustering; fuzzy simple; fuzzy slic; simple linear

Journal Title: IEEE Transactions on Circuits and Systems for Video Technology
Year Published: 2021

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.