Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.

Design and use of mobile technology in distance language education : Matching learning practices with technologies-in-practice

This thesis focuses on the adaptation of formal education to people’s technology- use patterns, theirtechnology-in-practice, where the ubiquitous use of mobile technologies is central. The research question is: How can language learning practices occuring in informal learning environments be effectively integrated with formal education through the use of mobile technology? The study investigates the technical, pedagogical, social and cultural challenges involved in a design science approach. The thesis consists of four studies. The first study systematises MALL (mobile-assisted language learning) research. The second investigates Swedish and Chinese students’ attitudes towards the use of mobile technology in education. The third examines students’ use of technology in an online language course, with a specific focus on their learning practices in informal learning contexts and their understanding of how this use guides their learning. Based on the findings, a specifically designed MALL application was built and used in two courses. Study four analyses the app use in terms of students’ perceived level of self-regulation and structuration. The studies show that technology itself plays a very important role in reshaping peoples’ attitudes and that new learning methods are coconstructed in a sociotechnical system. Technology’s influence on student practices is equally strong across borders. Students’ established technologies-in-practice guide the ways they approach learning. Hence, designing effective online distance education involves three interrelated elements: technology, information, and social arrangements. This thesis contributes to mobile learning research by offering empirically and theoretically grounded insights that shift the focus from technology design to design of information systems.