3D underwater monocular machine vision from 2D images in an attenuating medium

Files

Randell_CharlesJames_PhD_1997.pdf (4.19 MB)

Date

2017-05-25

Authors

Randell, Charles James

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

This dissertation presents a novel underwater machine vision technique which uses the optical properties of water to extract range information from colour images. By exploiting the fact that the attenuation of light in water is a function of frequency, an intensity-range transformation is developed and implemented to provide monocular vision systems with a three-dimensional scene reconstruction capability. The technique can also be used with images that have no salient, contrasting features and there are no restrictions on surface shapes. From a generalized reflectance map based on the optical properties of water, the closed form intensity-range transformation is derived to convert intensity images from various spectral bands into a range map wherein the value of each "pixel" is the range to the imaged surface. The technique is computationally efficient enough to be performed in real time and does not require specialized illumination or similar restrictive conditions. A calibration procedure is developed which enables the transformation to be practically implemented. An alternate approach to estimating range from multispectral data based on expanding the medium's transfer function and using these terms as elements in sensitivity vectors is also presented and analyzed. Mathematical analysis of the intensity-range transformation and associated developments is provided in terms of its performance in noise and sensitivity to various system parameters. Its performance as a function of light scattering is studied with the aid of computer simulation. Results from transforming actual underwater images are also presented. The results of this analysis and the demonstrated performance of the intensity-range transformation endorse it as a practical enhancement to underwater machine vision systems.

Description

Keywords

Computer vision, Image processing, Underwater light

Citation

URI

http://hdl.handle.net/1828/8194

Collections

ETD (Electronic Theses and Dissertations)
Theses (Electrical and Computer Engineering)
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.