Surveillance Applications: Image Recognition on the Internet of Things
Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
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.
Image recognition, computer vision, color histogram, camera, surveillance, smart applications, Internet of Things, MediaSense, cell phone, Android, Java, programming
IdentifiersURN: urn:nbn:se:miun:diva-18557OAI: oai:DiVA.org:miun-18557DiVA: diva2:608917
Computer Science TDATG 180 higher education credits
Forsström, Stefan, PhD.
Jennehag, Ulf, Dr.