摘要:
针对类人足球机器人存在识别运动目标效果差、容易受光照变化影响等问题,提出了一种基于颜色和形状的运动目标跟踪算法:在HSI空间执行基于颜色信息的快速阈值分割,获取目标信息,加入自适应阈值更新,以增加算法的鲁棒性;利用卡尔曼滤波预测运动目标下一帧的位置,在局部范围根据目标形状信息执行优化边缘检测识别目标,获取目标准确的位置信息,然后继续跟踪.实验证明:该算法能够对运动目标进行准确跟踪,可满足实时性的要求.
Abstract:
A moving object tracking algorithm based on the color information and shape information was proposed,for the humanoid soccer shows poor performance on detecting moving object effect and is easily affected by the variable illumination.It implements rapid image threshold segmentation based on color information in the HSI color space,obtains the object information,and was joined by the adaptive threshold update to improve the robustness of algorithm.The possible position of the moving object in the next frame is predicted by Kalman filter,then,according to the shape information,implements optimizing edge detection to recognize the object in local area,obtains the accurate object location information in the image,then continues to track.The experiments show that this algorithm can accurately track the moving object,satisfy the requirement of the real-time.