A new target detection algorithm of ViBe based on phased improvement

Abstract:

In view of the problems of ghost and incomplete detection in the process of target detection in the visual background extractor (ViBe) algorithm, this paper proposes a new algorithm of target detection of ViBe based on phased improvement.Firstly, in the initial phase of the model, the background model is constructed using the average value of the corresponding pixels of the first m frames of video sequence.At the same time, the 8 neighborhood of the original algorithm is changed to 24 neighborhood for sample selection and dynamic adjustment of the matching radius; then in the target detection stage, the maximum inter class difference method is introduced to calculate the best segmentation threshold of the current frame, and then the foreground pixels are discriminated twice; Secondly, in the phase of background model updating, the size of updating factor is dynamically adjusted according to the speed of background change; finally, the final foreground target is obtained by morphological processing of the obtained foreground image.Experimental results show that the improved ViBe algorithm not only solves the ghost problem effectively, but also improves the accuracy and integrity of target detection.