Traffic Sign Detection Based on Video Encoding Stream

oleh: Jingjing YANG, Fujiang LI, Qigui ZHANG

Format: Article
Diterbitkan: Editorial Office of Journal of Taiyuan University of Technology 2022-01-01

Deskripsi

In order to improve the poor real-time performance of traffic sign detection in natural scenes, a traffic sign detection method based on video stream was proposed. This method makes full use of the correlation between the pixels of the coding block, and the different color and edge characteristics of traffic signs that can be reflected in the code stream. By analyzing the intra-frame prediction mode, the value of coded_block_pattern, and the pixel residual information, the traffic signs are initially located. By analyzing the prediction mode of the inter-frame, the value of coded_block_pattern, and the motion vector information, the traffic sign detection is corrected. This method avoids time-consuming operations such as integer discrete cosine transform (IDCT), inverse quantization, reconstruction, and loop filtering in video decoding process. The experiment based on the China Traffic Sign Database (CCTSDB) obtained 96.9% detection rate and 4.3% false detection rate. The detection time of this method is greatly shortened and can meet the real-time detection requirements.