A Road Sign Recognition System on Raspberry Pi

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Road Sign Recognition System

Digital image processing, i.e. the use of computer systems to process pictures, has applications in many fields, including of medicine, space exploration, geology and oceanography and continues to increase in its applicability.

The main objective of this project is to demonstrate the ability of image processing algorithms on a small computing platform. Specifically I created a road sign recognition system based on an embedded system, that reads and recognizes speed signs. The project report describes the characteristics of speed signs, requirements and difficulties behind implementing real-time base system with embedded system, how to deal with numbers using image processing techniques based on shape and dimension analysis. The system also shows the techniques used for classification and recognition.

Color analysis plays a specifically important role in many other different applications for road sign detection, this report points to many problems regarding stability of color detection due to daylight conditions, so absence of color model can led a better solution.

Neural networks are also widely used techniques in road sign detection and recognition. Additionally some other techniques such as template matching and classical classifiers were also employed, however in this project light-weight techniques were mainly used due to limitation of real- time based application and Raspberry Pi capabilities. Raspberry Pi is the main target for the implementation, as it provides an interface between sensors, database, and image processing results, while also performing functions to manipulate peripheral units (usb dongle, keyboard etc.).