Abstract：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.
［1］魏宁.篮球运动视频分析系统初步研究［D］. 青岛:青岛科技大学, 2013.
［2］王千.基于视频的篮球持球队员行为预测研究［D］. 长沙:中南大学, 2012.
［3］Zamalieva D, Yilmaz A. Background subtraction for the moving camera: A geometric approach［J］. Computer Vision and Image Understanding, 2014, 127(10):73-85.
［4］郑佳,李江勇. 基于背景差分和信息熵的运动目标检测算法［J］. 激光与红外, 2014, 44(5):563-566.
［5］Malmberg F, Hendriks C L L. An efficient algorithm for exact evaluation of stochastic watersheds［J］. Pattern Recognition Letters, 2014, 47(10):80-84.
［6］Crammond G, Boyd S W, Dulieu-Barton J M. Speckle pattern quality assessment for digital image correlation［J］. Optics and Lasers in Engineering, 2013, 51(12):1368-1378.
［7］Chen H T, Chou C L, Fu T S, et al. Recognizing tactic patterns in broadcast basketball video using player trajectory［J］. Journal of Visual Communication and Image Representation, 2012, 23(6):932-947.
［8］Chen H T, Tian M C, Chen Y W, et al. Physics-based ball tracking and 3D trajectory reconstruction with applications to shooting location estimation in basketball video［J］. Journal of Visual Communication and Image Representation, 2009, 20(3):204-216.
［9］Hiroki Okubo, Mont Hubbard. Dentification of basketball parameters for a simulation model［J］. Procedia Engineering, 2010, 2(6):3281-3286.
［10］Fan Chen, Christophe De Vleeschouwer. Personalized production of basketball videos from multi-sensored data under limited display resolution［J］. Computer Vision and Image Understanding, 2010, 114(6): 667-680.
［11］吴凤和,王金芬,王军,等. 基于阈值分割与多边形扫描求交的明暗恢复形状重构模型冗余信息去除［J］. 计量学报, 2014, 35(1): 44-48.
［12］Soleimanpour-moghadam M, Nezamabadi-pour H, Farsangi M M. A quantum inspired gravitational search algorithm for numerical function optimization［J］. Information Sciences, 2014, 267(20):83-100.
［13］Tsai J, Hsiao F Y, Li Y J, et al. A quantum search algorithm for future spacecraft attitude determination［J］. Acta Astronautica, 2011, 68(7-8):1208-1218.
［14］Li P C, Li S Y. A Grover quantum searching algorithm based on the weighted targets［J］. Journal of Systems Engineering Electronics, 2008, 19(2):363-369.
［15］Anwar M S, Blazina D, Carteret H A, et al. Implementing Grover’s quantum search on a para-hydrogen based pure state NMR quantum computer［J］. Chemical Physics Letters, 2004, 400(11):94-97.
［16］Luan L L, Wang Z J, Liu S M. Progress of Grover Quantum Search Algorithm［J］. Energy Procedia, 2012, 16(C): 1701-1706.
［17］Liu Y P, Koehler G J. Using modifications to Grover’s Search algorithm for quantum global optimization［J］. European Journal of Operational Research, 2010, 207(2):620-632.
［18］Joonwoo Bae, Kwon Y, Baek I, et al. Interaction-aided continuous time quantum search［J］. Chaos, Solitons & Fractals, 2005, 24(1):103-106.
［19］Sebastian Drn, Thomas Thierauf. A note on the search for k elements via quantum walk［J］. Information Processing Letters, 2010, 110(22): 975–978.
2015, Vol. 36 
