Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Surveillance Applications: Image Recognition on the Internet of Things
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This is a B.Sc. thesis within the Computer Science programme at the Mid Sweden University. The purpose of this project has been to investigate the possibility of using image based surveillance in smart applications on the Internet-of-Things. The goals involved investigating relevant technologies and designing, implementing and evaluating an application that can perform image recognition. A number of image recognition techniques have been investigated and the use of color histograms has been chosen for its simplicity and low resource requirement. The main source of study material has been the Internet. The solution has been developed in the Java programming language, for use on the Android operating system and using the MediaSense platform for communication. It consists of a camera application that produces image data and a monitor application that performs image recognition and handles user interaction. To evaluate the solution a number of tests have been performed and its pros and cons have been identified. The results show that the solution can differentiate between simple colored stick figures in a controlled environment. Variables such as lighting and the background are significant. The application can reliably send images from the camera to the monitor at a rate of one image every four seconds. The possibility of using streaming video instead of images has been investigated but found to be difficult under the given circumstances. It has been concluded that while the solution cannot differentiate between actual people it has shown that image based surveillance is possible on the IoT and the goals of this project have been satisfied. The results were expected and hold little newsworthiness. Suggested future work involves improvements to the MediaSense platform and infrastructure for processing and storing data.

Place, publisher, year, edition, pages
2013. , 25 p.
Keyword [en]
Image recognition, computer vision, color histogram, camera, surveillance, smart applications, Internet of Things, MediaSense, cell phone, Android, Java, programming
National Category
Computer Science
Identifiers
URN: urn:nbn:se:miun:diva-18557OAI: oai:DiVA.org:miun-18557DiVA: diva2:608917
Educational program
Computer Science TDATG 180 higher education credits
Uppsok
Technology
Supervisors
Examiners
Projects
MediaSense
Available from: 2013-03-27 Created: 2013-03-01 Last updated: 2013-03-27Bibliographically approved

Open Access in DiVA

Surveillance Applications(820 kB)295 downloads
File information
File name FULLTEXT01.pdfFile size 820 kBChecksum SHA-512
6cd09bb4debd5776794a988b577e2197069b44ac9f56112600249742f087bf9543109478b7f72302db5d46a0d14451af10d3d0c8fd20e2e2954dc3d0ceb4e98d
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Rönnqvist, Patrik
By organisation
Department of Information Technology and Media
Computer Science

Search outside of DiVA

GoogleGoogle Scholar
Total: 295 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 403 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf