Recognition of Vehicle Based on RVM and Direction Derivative Function
Because large picture base must be initially established for image match and image recognition is seriously dependent on gray scale gradient,this paper adopts relative vector machine and direction derivative function of gray scale to recognize vehicle.The results show that the presented model has only limited picture base and search capacity is small.Furthermore, the recognition consuming time of this model is short and has high accuracy.The model is little dependent on gray scale gradient and the fake outline pixels can be removed by double thresholds.In addition, the thinning vehicle outline edge is accomplished.
relative vector machine direction derivative function thresholds thinning
Cui Yu Huang Xiaomeng
Changan University, School of Automobile, Xian 710064, China
国际会议
西安
英文
427-430
2015-09-18（万方平台首次上网日期，不代表论文的发表时间）