Background Modeling by Combining Joint Intensity Histogram with Time-sequential Data
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Background images are identified by analyzing the changes in texture of the image sequences. According to the characteristics of highway traffic scenes, in this paper, the author presents a new algorithm for identifying background image based on the gradient projection statistics of the binary image. First, the images are blocked by road lane, and the background is identified by projection statistics and projection gradient statistics of the sub-images. Second, the background is reconstructed according to the results of each sub-image. Experimental results show that the proposed method exhibits high accuracy for background identification and modeling. In addition, the proposed method has a good anti-interference to the low intensity vehicles, and the processing time is less as well. The speed ??and accuracy of the proposed algorithm meets the needs of video surveillance system requirements for highway traffic scenes.