| Summary: | 碩士 === 中原大學 === 電子工程研究所 === 103 === In this study, a speed sign detection and digit recognition system is proposed based on image processing techniques. The proposed system can remind the driver of speed limits automatically to avoid traffic violation and keep driving safe.
The system mainly utilizes the information of color features, along with shape features, to detect speed signs. First, we use the HSV color space to detect the speed sign with a red boarder. To avoid the influence of different weather or light conditions, we apply an adaptive threshold operation to deal with the images taken from various light conditions such that the captured images are automatically divided into two cases: day and night. When the detection event occurs at night, the proposed method will enhance the image of the traffic signs for a better result, followed by the detection of circle features with Hough transform. If the circle size is in the setting range, it is considered as a speed sign. Furthermore, image enhancement and feature extraction in the CMYK color space together with morphology operations are utilized to effectively cut out the digit part of a speed sign. Then the characters in the speed sign will be recognized by the retrained OCR software called Tesseract-OCR.
We recoded the videos while driving by a commercial event data recorder (EDR) to evaluate the performance of the proposed method. The recoded videos contain several weather conditions such as sunny, cloudy, dusky, and rainy days. The experimental results show that, in the conditions of no rain and day time, the detection and recognition rate for speed signs is 92%, while it is 80% at night. Finally, the proposed system runs on a personal computer to perform the tasks of detection and recognition for the images containing speed signs, and it takes only 0.2~0.4 seconds to generate the information of speed limit.
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