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A Difference Tracking Algorithm Based on Discrete Sine Transform

机译：基于离散正弦变换的差分跟踪算法

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摘要

Target tracking is an important field of computer vision. The template matching tracking algorithm based on squared difference matching (SSD) and standard correlation coefficient (NCC) matching is very sensitive to the gray change of image. When the brightness or gray change, the tracking algorithm will be affected by high-frequency information. Tracking accuracy is reduced, resulting in loss of tracking target. In this paper, a differential tracking algorithm based on discrete sine transform is proposed to reduce the influence of image gray or brightness change. The algorithm that combines the discrete sine transform and the difference algorithm maps the target image into a image digital sequence. The Kalman filter predicts the target position. Using the Hamming distance determines the degree of similarity between the target and the template. The window closest to the template is determined the target to be tracked. The target to be tracked updates the template. Based on the above achieve target tracking. The algorithm is tested in this paper. Compared with SSD and NCC template matching algorithms, the algorithm tracks target stably when image gray or brightness change. And the tracking speed can meet the read-time requirement.
机译：目标跟踪是计算机视觉的重要领域。基于平方差匹配（SSD）和标准相关系数（NCC）匹配的模板匹配跟踪算法对图像的灰度变化非常敏感。当亮度或灰度改变时，跟踪算法将受到高频信息的影响。跟踪精度降低，导致跟踪目标丢失。为了减少图像灰度或亮度变化的影响，提出了一种基于离散正弦变换的差分跟踪算法。结合离散正弦变换和差分算法的算法将目标图像映射到图像数字序列。卡尔曼滤波器可预测目标位置。使用汉明距离确定目标和模板之间的相似度。最接近模板的窗口确定要跟踪的目标。要跟踪的目标将更新模板。基于以上实现目标跟踪。本文对该算法进行了测试。与SSD和NCC模板匹配算法相比，该算法可以在图像灰度或亮度变化时稳定地跟踪目标。并且跟踪速度可以满足读取时间的要求。

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