NDLI: Detail-enhanced target segmentation method for thermal video sequences based on spatiotemporal parameter update technique

Content Provider	IET Digital Library
Author	Yang, Dong Won
Abstract	Thermal images have been widely used for detection, tracking, and classification of targets at night for military purpose. A thermal imaging sensor receives the radiation energy from the target and the background, so it has advantages in night vision. However, the thermal images have lower spatial resolution and more blurred edges than colour images, and edges can be contaminated by flames. Therefore, the extracted edges which can be used in automatic target classification may contain inaccurate edges that can decrease the accuracy of the classification. In this study, to overcome these problems, a novel background modelling method based on spatiotemporal parameter updating technique and foreground detection method using intensity moments analysis is proposed. To validate the proposed method, thermal images with military vehicle targets (tank and infantry vehicle) and public dataset in CDNET2014 (www.changedetection.net) are used in subjective and objective tests, respectively. The experiment results showed that the proposed method outperformed the state-of-the-art methods in objective measures and in subjective measure especially on detail-enhanced segmentation.
Starting Page	216
Ending Page	223
Page Count	8
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 1, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5341
Journal	IET Image Processing
Publisher Date	2018-10-31
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Target Classification Background Modelling Method Blurred Edges CDNET2014 Public Dataset Computer Vision And Image Processing Technique Detail-enhanced Target Segmentation Edge Detection Extracted Edge Foreground Detection Method Image Motion Analysis Image Recognition Image Resolution Image Segmentation Image Sequence Image Sonsor Infantry Vehicle Infrared Imaging Intensity Moments Analysis Military Vehicle Military Vehicle Targets Night Vision Object Detection Radiation Energy Spatial Resolution Spatiotemporal Parameter Spatiotemporal Parameter Updating Technique Target Segmentation Method Thermal Image Thermal Imaging Sensor Thermal Video Sequence
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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