Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

Detection of floating mines in infrared sequences by multiscale geometric filtering

[+] Author Affiliations
Dominique Florins, Antoine Manzanera

Ecole Nationale Supérieure de Techniques Avancées (France)

Proc. SPIE 8357, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII, 83571Q (May 1, 2012); doi:10.1117/12.918420
Text Size: A A A
From Conference Volume 8357

  • Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII
  • J. Thomas Broach; John H. Holloway
  • Baltimore, Maryland, USA | April 23, 2012

abstract

Automatic detection of oating mines by passive sensing is of major interest, yet remains a hard problem. In this paper, we propose an algorithm to detect them in infrared sequences, based on their geometry, provided by spatial derivatives. In infrared images, oating mines contrast with the sea due to the dierence of emissivity at low incidence angles: they form bright elliptical areas. Using the available data and the geometry of our camera, we rst determine the scales of interest, which represent the possible size of mines in number of pixels. Then, we use a temporal and a morphological lter to perform smoothing in the time dimension and contrast enhancement in the space dimensions, at the selected scales, and calculate for every pixel the Hessian matrix, composed of the second order derivatives, which are estimated in the classical scale-space framework, by convolving the image with derivatives of Gaussian. Based on the eigenvalues of the Hessian matrix, representing the curvatures along the principal directions of the image, we dene two parameters describing the eccentricity of an elliptical area and the contrast with sea, and propose a measure of mine-likeliness" that will be high for bright elliptical regions with selected eccentricy. At the end, we only retain pixels with high mine-likeliness, stable in time, as potential mines. Using a dataset of 10 sequences with ground truth, we evaluated the performance and stability of our algorithm, and obtained a precision between 80% and 100%, and a per-frame recall between 30% and 100%, depending on the diculty of the scenarios.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Dominique Florins and Antoine Manzanera
"Detection of floating mines in infrared sequences by multiscale geometric filtering", Proc. SPIE 8357, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVII, 83571Q (May 1, 2012); doi:10.1117/12.918420; http://dx.doi.org/10.1117/12.918420


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement


  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.