A real-time image understanding system for an autonomous mobile robot
By: Leonard V. Remias
Contributors: Naval Postgraduate School (U.S.)
Publisher: Naval Postgraduate School
Published: 1996
Place of publication: Monterey, California
Language: eng
Format: Electronic resource
Number of pages: 129
Subjects: Algorithms; Computer vision; Robotics; Image processing; Computer science
Description: Yamabico-11 is an autonomous mobile robot used as a research platform with one area in image understanding. Previous work focused on edge detection analysis on a Silicon Graphics Iris (SGI) workstation with no method for implementation on the robot. Yamabico-11 does not have an on-board image processing capability to detect straight edges in a grayscale image and a method for allowing the user to analyze the data. The approach taken for system development is partly based on edge extraction and line fitting algorithms of (PET92) with a 3-D geometric model of the robot's world (STE92). Image grabbing routines of (KIS95) were used to capture images with the robot's digital output camera and processed using image understanding routines developed for a SGI workstation. The routines were modified and ported onto the robot. The new method of edge extraction produces less ambient noise and more continuous vertical line segments in the gradient image which enhances pattern matching analysis of the image. Yamabico-11's computer system can capture an image with a resolution of 739 x 484 active picture elements. Edge detection analysis is performed on the robot which generates a list structure of edges and stored in the robot's memory for user analysis.
Notes: Thesis Advisor(s): Kanayama, Yutaka  ; Second Reader: Lee, Chin-Hwa.

"March 1996."

Author(s) subject terms: Robotics, Computer Vision, Edge Extraction, Obstacle Avoidance, Image Understanding.

Description based on title screen as viewed on September 23, 2010.

DTIC Descriptor(s): Image Processing, Real Time, Robots, Computer Vision, Algorithms, Robotics, Detection, Edges, Theses, Memory Devices, Platforms, Silicon, Mobile, Images, Self Operation, Patterns, Graphics, User Needs, Work Stations, Extraction, Systems Approach, Matching, Ambient Noise, Onboard, Gradients, Gray Scale.

DTIC Identifier(s): Image Understanding, SGI(Silicon Graphics Iris), Obstacle Avoidance.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 1996.

Includes bibliographical references (p.127-128).

"Approved for public release, distribution unlimited"--Cover.

Also available in print.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

US Navy (USN) author.

record replaced 9/23/10. rb

dk/dk cc:9996 11/8/96