Next Article in Journal
Printable Electrochemical Biosensors: A Focus on Screen-Printed Electrodes and Their Application
Next Article in Special Issue
Correction: Liu, B., et al. Quantitative Evaluation of Pulsed Thermography, Lock-In Thermography and Vibrothermography on Foreign Object Defect (FOD) in CFRP. Sensors 2016, 16, doi:10.3390/s16050743
Previous Article in Journal
Underwater Sensor Network Redeployment Algorithm Based on Wolf Search
Previous Article in Special Issue
A Ground-Based Near Infrared Camera Array System for UAV Auto-Landing in GPS-Denied Environment
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(10), 1756; doi:10.3390/s16101756

A Novel Gradient Vector Flow Snake Model Based on Convex Function for Infrared Image Segmentation

Department of Measurement Control and Information Technology, School of Instrumentation Science and Optoelectronics Engineering, Beihang University, Beijing 100191, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vincenzo Spagnolo
Received: 7 July 2016 / Revised: 24 August 2016 / Accepted: 21 September 2016 / Published: 21 October 2016
(This article belongs to the Special Issue Infrared and THz Sensing and Imaging)
View Full-Text   |   Download PDF [8776 KB, uploaded 21 October 2016]   |  

Abstract

Infrared image segmentation is a challenging topic because infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow, have several advantages in terms of infrared image segmentation. However, the GVF (Gradient Vector Flow) model also has some drawbacks including a dilemma between noise smoothing and weak edge protection, which decrease the effect of infrared image segmentation significantly. In order to solve this problem, we propose a novel generalized gradient vector flow snakes model combining GGVF (Generic Gradient Vector Flow) and NBGVF (Normally Biased Gradient Vector Flow) models. We also adopt a new type of coefficients setting in the form of convex function to improve the ability of protecting weak edges while smoothing noises. Experimental results and comparisons against other methods indicate that our proposed snakes model owns better ability in terms of infrared image segmentation than other snakes models. View Full-Text
Keywords: active contour model; gradient vector flow; infrared image segmentation; external force field active contour model; gradient vector flow; infrared image segmentation; external force field
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Zhang, R.; Zhu, S.; Zhou, Q. A Novel Gradient Vector Flow Snake Model Based on Convex Function for Infrared Image Segmentation. Sensors 2016, 16, 1756.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top