Highway Background Identification and Background Modeling Based on Projection Statistics

Highway Background Identification and Background Modeling Based on Projection Statistics

Jun Zhang (Tianjin University, China)
Copyright: © 2013 |Pages: 9
DOI: 10.4018/978-1-4666-2645-4.ch024
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Abstract

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.
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2. Background Identification Based On Statistics

2.1. Highway Scene Features

We can find that the road is flat, the color is single and texture information is not obvious in the background images, while the color is rich and texture information is obvious in the Vehicle images, from the image sequences. The reason is that the edge of the vehicle front part in images is rich, such as the lights, heat sinks, plates, etc., which is depicted in Figure 1. According to this feature of the highway image sequences, firstly this paper identifies the background images roughly. Secondly, do the background modeling using the images of the previous step results.

Figure 1.

Background images contrast with the vehicle images

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