2000-fps multi-object extraction based on cell-based labeling

Real-time multi-object extraction at 2000 fps was realized by designing a cell-based labeling algorithm. The algorithm can label the divided cells in an image by scanning the image only once to obtain their moment features, and the computational complexity required for labeling can be remarkably reduced. The cell-based labeling algorithm for 8 × 8 pixel cells was implemented on a high-speed vision platform, and multiple objects in an image of 512 × 512 pixels could be extracted at 2000 fps. An experiment was performed using a quickly rotating object to verify the performance of our multi-object extraction system.