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Massachusetts Institute of Technology

High-speed optics based depth mapping for automated active safety system

Abstract

dc:description.abstract

The usage of image processing in automotive active safety systems has increased dramatically in the recent decades. Main interest of the digital signal processing has been in the area of communications or networks, but with various advancements in the digital image processing, new type of applications has become possible. The advancement of digital camera technology along with the fast pace of development of faster microprocessors, it has become possible to implement more advanced image processing tasks for high-speed applications. The availability of image processing results in a timely fashion opens up new possibilities. In this project, sponsored by Ford, we will look at the use of machine vision system to build a standalone system capable of providing real-time depth map for automated emergency brake systems in cars.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2016

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kim, JooHun
Advisor dc:contributor.advisor
  • Kamal Youcef-Toumi.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/117859
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/117859

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Kim, JooHun. High-speed optics based depth mapping for automated active safety system. Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/117859