Implementation of a Labeling Algorithm based on Contour Tracing with Feature Extraction

This paper describes an architecture of a connected-cluster labeling algorithm for binary images based on contour tracing with feature extraction. The implementation is intended as a hardware accelerator in a self contained real-time digital surveillance system. The algorithm has lower memory requirements compared to other labeling techniques and can guarantee labeling of a predefined number of clusters independent of their shape. In addition, features especially important in this particular application are extracted during the contour tracing with little increase in hardware complexity. The implementation is verified on an FPGA in an embedded system environment with an image resolution of 320 times 240 at a frame rate of 25 fps. The implementation supports labeling of 61 independent clusters, extracting their location, size and center of gravity.