Next Article in Journal
A Study on AIN Film-Based SAW Attenuation in Liquids and Their Potential as Liquid Ethanol Sensors
Next Article in Special Issue
Efficient Pedestrian Detection at Nighttime Using a Thermal Camera
Previous Article in Journal
An Ultra-Low Power Turning Angle Based Biomedical Signal Compression Engine with Adaptive Threshold Tuning
Previous Article in Special Issue
Person Recognition System Based on a Combination of Body Images from Visible Light and Thermal Cameras
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(8), 1811;

Thermal Infrared Pedestrian Image Segmentation Using Level Set Method

School of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
Author to whom correspondence should be addressed.
Received: 7 July 2017 / Revised: 1 August 2017 / Accepted: 3 August 2017 / Published: 6 August 2017
Full-Text   |   PDF [6820 KB, uploaded 14 August 2017]   |  


The edge-based active contour model has been one of the most influential models in image segmentation, in which the level set method is usually used to minimize the active contour energy function and then find the desired contour. However, for infrared thermal pedestrian images, the traditional level set-based method that utilizes the gradient information as edge indicator function fails to provide the satisfactory boundary of the target. That is due to the poorly defined boundaries and the intensity inhomogeneity. Therefore, we propose a novel level set-based thermal infrared image segmentation method that is able to deal with the above problems. Specifically, we firstly explore the one-bit transform convolution kernel and define a soft mark, from which the target boundary is enhanced. Then we propose a weight function to adaptively adjust the intensity of the infrared image so as to reduce the intensity inhomogeneity. In the level set formulation, those processes can adaptively adjust the edge indicator function, from which the evolving curve will stop at the target boundary. We conduct the experiments on benchmark infrared pedestrian images and compare our introduced method with the state-of-the-art approaches to demonstrate the excellent performance of the proposed method. View Full-Text
Keywords: thermal pedestrian images; active contour model; level set method; one-bit transform; edge indicator function thermal pedestrian images; active contour model; level set method; one-bit transform; edge indicator function

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).

Share & Cite This Article

MDPI and ACS Style

Qiao, Y.; Wei, Z.; Zhao, Y. Thermal Infrared Pedestrian Image Segmentation Using Level Set Method. Sensors 2017, 17, 1811.

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



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