Fast connected component labeling algorithm using a divide and conquer technique

We investigate a method to speed up the O(n3 ) labeling algorithm of Rosenfeld and Pfaltz for segmenting binary images, which is unduly complex for large images. That algorithm searches line-by-line, top to bottom, to assign a blob label to each current pixel that is connected to a blob. A large number K of labels arises of which many are equivalent, so the equivalence must be resolved. This requires a KxK matrix to represent the connectivity and O(K3 ) operations for resolution, which is very large for large images. Our approach partitions the binary image into NxN rectangles and perform local equivalence resolution on each while keeping track of the global equivalence with list pointers to equivalence lists. Such divide and conquer technique greatly increases the run time speed.

• Type: Conference
• Year: 2000
• Where: CATA
• Authors: June-Me Park, Carl G. Looney, Hui-Chuan Chen
• Keywords: Binary Image, CATA 2000, CATA 2007, Large Images, Local Equivalence Resolution