摘要
为提高篮球图像分割效果，提出了量子搜索算法（QSA）。首先建立篮球分割模型，包括基于3级尺度级的篮球球心、半径建模，基于灰度概率分布的篮球目标分割建模；然后进行量子相位Grover变换，构建加权因子与篮球目标关系，确定最大量子搜素成功概率与量子旋转相位的角度；最后给出了算法流程。实验仿真表明：该算法能有效完成篮球对象的分割，同时分割成功率较高。
In order to improve the effect of basketball image segmentation, quantum search algorithm （QSA） is proposed. Firstly, basketball segmentation model was established, including basketball center and radius based on three scales, and basketball target was segmented based on gray probability distribution. Secondly, quantum phase was transformed based on quantum phase Grover conversion in order to establish weighting factor and basketball target relation, and maximum quantum search success possibility and angle of quantum rotation phase was determined. Finally, quantum search algorithm process was given. Simulation indicated that quantum search algorithm can accomplish basketball object segmentation effectively, and segmentation success rate is higher.
出处
《计量学报》
CSCD
北大核心
2015年第5期464-468,共5页
Acta Metrologica Sinica
基金
河南省科技厅重点研究项目(9412011Y1330)
关键词
计量学
量子搜索算法
篮球图像分割
旋转相位
权系数
metrology
quantum search algorithm
basketball image segmentation
rotation phase
weight coefficient
