CAJ | 학술논문

提出一种基于四元数傅里叶变换注意力选择和脉冲耦合神经网络在图像中跟踪足球的方法.首先进行图像预处理以去除球场以外的区域,用四元数注意力选择算法提取感兴趣区域,基于颜色、形状、面积等多种特征检测足球.若检测失败,则采用卡尔曼滤波器预测足球位置.仿真结果表明,与基于速度控制的动态卡尔曼滤波和实时足球检测两种方法相比,检测成功率分别提高9.6%和14.9%.
제출일충기우사원수부리협변환주의력선택화맥충우합신경망락재도상중근종족구적방법.수선진행도상예처리이거제구장이외적구역,용사원수주의력선택산법제취감흥취구역,기우안색、형상、면적등다충특정검측족구.약검측실패,칙채용잡이만려파기예측족구위치.방진결과표명,여기우속도공제적동태잡이만려파화실시족구검측량충방법상비,검측성공솔분별제고9.6%화14.9%.
@@@@This paper proposes a soccer detection method that combines the attention selection model of phase spectrum of quaternion Fourier transform (PQFT) and pulse coupled neural network (PCNN). In the preprocessing, the region outside the field is removed, and the region of interest extracted using PQFT. The target is detected according to the physical characteristics such as color, shape and size. If no candidate or more than one are detected, a Kalman filter is used to make prediction. Simulation shows that the identification rate is improved by 9.6% and 14.9% respectively as compared to the dynamic Kalman filtering with velocity control and the real time ball detection framework introduced in the literature.