Genetic particle filter via Harris and its application in license plate tracking
To solve the problem of population diversity attenuation,low efficiency and accuracy of traditional particle filter,the genetic operation is applied to optimize its resampling process.Specifically,after resampling,each particle is arranged by the fitness value,and then the samples with fitness lower than the average value are replaced by the samples randomly selected from the particles with better fitness,and then the genetic operation is introduced to cross and mutate the particles to complete the update of the sample set.Meanwhile,the gray and color histogram features commonly used in traditional visual target tracking are very vulnerable to background color interference,very sensitive to illumination changes and has a large amount of calculation.So Harris features with the characteristics of easy extraction,small amount of calculation,anti rotation or inclination angle influence,strong anti-interference,uniform distribution,accurate positioning and high stability are introduced to cooperate with the genetic particle filter tracking framework,and a visual tracking algorithm with high robustness is obtained.The proposed genetic particle filter tracker based on Harris features is applied to the highway vehicle license plate tracking experiment.The application results prove that the method has high precision and high numerical stability,and can complete the precise tracking of the vehicle license plate in the case of rapid target movement,sharp changes in light and background.
万方数据
维普
