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Author Malinoski, Phillip, author.
Title Object detection and recognition for UAV / by Phillip Malinoski.
Published [Northridge, California] : California State University, Northridge, 2012.
LOCATION CALL # STATUS
 Electronic Book  QA76 .Z95 2012 M35eb    ONLINE
  
Description 1 online resource (viii, 64 pages) : illustrations, color.
Content Type text
still image
Format online resource
File Characteristics text file PDF
Thesis M.S. California State University, Northridge 2012.
Bibliography Includes bibliographical references (page 64).
Summary Unmanned aerial vehicle systems have grown increasingly advanced in not only mechanical performance and power, but in intelligence as well. As software capabilities increase, it is expected that these systems respond to complex situations in ways that humans cannot. Although often tasked with several assignments, object detection and recognition is one that can contribute a great deal of information. Using computer vision as source for environmental data, this project attempts a small prototypical system for identifying objects that it discovers. The project goal was to develop a prototype to be used in an unmanned aerial vehicle competition to detect, identify, and report ground objects during flight. This prototype detects 75 to 90 percent of the objects, correctly identifies 80 percent of the objects, and reports information about the classified objects. The system uses OpenCV, Perl scripting, and cURL software libraries. This report describes the requirements, success, and suggestions for the prototype.
Note Description based on online resource; title from PDF title page (viewed on May 30, 2012).
Subject Pattern recognition systems -- Design and construction.
Drone aircraft.
Computer vision.
Local Subject Dissertations, Academic -- CSUN -- Computer Science.
Alternate Title Object detection and recognition for unmanned aerial vehicles
OCLC number 847538279