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Moving Vehicle Detection in Traffic Video Using Modified SXCS-LBP Texture Descriptor
Abstract
In this chapter, the authors proposed background modeling and subtraction-based methods for moving vehicle detection in traffic video using a novel texture descriptor called Modified Spatially eXtended Center Symmetric Local Binary Pattern (Modified SXCS-LBP) descriptor. The XCS-LBP texture descriptor is sensitive to noise because in order to generate binary code, the value of center pixel value is used as the threshold directly, and it does not consider temporal motion information. In order to solve this problem, this chapter proposed a novel texture descriptor called Modified SXCS-LBP descriptor for moving vehicle detection based on background modeling and subtraction. The proposed descriptor is robust against noise, illumination variation, and able to detect slow moving vehicles because it considers both spatial and temporal moving information. The evaluation is carried out using precision and recall metric, which is obtained using experiments conducted on popular dataset such as BMC dataset. The experimental result shows that the method outperforms existing methods.
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