摘要
跟踪研究神经丝在生物医学神经退行疾病领域有重要意义,针对人工标记效率低的现状,提出用计算机自动跟踪神经丝。本文采用Kalman滤波算法和Mean Shift算法对荧光显微下神经丝蛋白质运动视频进行目标跟踪,跟踪结果表明,基于运动模型和估计测量值的Kalman滤波算法在跟踪效果上明显优于基于颜色空间特征的Mean Shift算法。
Tracking research on neurofilament plays an important role in biomedical neurodegenerative diseases.in view of the low efficiency of manual marking, it is proposed to use computer to track neurofilament automatically. in this paper, Kalman filtering and Mean Shift are used to track the neurofilament in the fluorescence microscopy video. The tracking results show that Kalman filtering based on motion model and measured estimation is superior to Mean Shift based on color feature in tracking effect.
作者
涂雪滢
Tu Xueying(School of Mechanical Engineering,Xinjiang university,urumqi 83004)
出处
《现代制造技术与装备》
2018年第7期24-25,共2页
Modern Manufacturing Technology and Equipment
