Combining Kalman Filter with Mixture Color Model Tracking of Pallet Image

In this paper, we propose combining the mixture color model with Kalman filter method. The purpose is to enable forklifts to search for pallets, but it is able to meet fully automated system with real-time. We focused on pallets for image feature and tracking. First, we manually segmented 30 pallet images and statistics of the best color threshold, this method must find the threshold of different color space and mixture of two important color spaces containing HSV and YCbCr, we extracted the H and the Cb composition mixtures to find the best color threshold, and using a combination of Kalman filter(KF) and the color model method to track pallet images, we then used the logic function to keep our information after obtaining the color image segmentation, the noise of the image must be removed, this algorithm can be used on video sequences efficiently. Finally, experimental results show that the method has effective tracking pallet images in the video sequences.