Feature based recognition of submerged objects in holographic imagery

Christopher R. Ratto, Nathaniel Beagley, Kevin C. Baldwin, Kara R. Shipley, Wayne I. Sternberger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The ability to autonomously sense and characterize underwater objects in situ is desirable in applications of unmanned underwater vehicles (UUVs). In this work, underwater object recognition was explored using a digital holographic system. Two experiments were performed in which several objects of varying size, shape, and material were submerged in a 43,000 gallon test tank. Holograms were collected from each object at multiple distances and orientations, with the imager located either outside the tank (looking through a porthole) or submerged (looking downward). The resultant imagery from these holograms was preprocessed to improve dynamic range, mitigate speckle, and segment out the image of the object. A collection of feature descriptors were then extracted from the imagery to characterize various object properties (e.g., shape, reflectivity, texture). The features extracted from images of multiple objects, collected at different imaging geometries, were then used to train statistical models for object recognition tasks. The resulting classification models were used to perform object classification as well as estimation of various parameters of the imaging geometry. This information can then be used to inform the design of autonomous sensing algorithms for UUVs employing holographic imagers.

Original languageEnglish (US)
Title of host publicationDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX
PublisherSPIE
ISBN (Print)9781628410099
DOIs
StatePublished - 2014
EventDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX - Baltimore, MD, United States
Duration: May 5 2014May 7 2014

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9072
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherDetection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX
CountryUnited States
CityBaltimore, MD
Period5/5/145/7/14

Keywords

  • Holography
  • feature extraction
  • image processing
  • object recognition
  • unmanned underwater vehicles

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Ratto, C. R., Beagley, N., Baldwin, K. C., Shipley, K. R., & Sternberger, W. I. (2014). Feature based recognition of submerged objects in holographic imagery. In Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIX [907205] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9072). SPIE. https://doi.org/10.1117/12.2049742