Tuyển tập các báo cáo nghiên cứu về hóa học được đăng trên tạp chí hóa hoc quốc tế đề tài : Efficient scan mask techniques for connected components labeling algorithm | Sutheebanjard and Premchaiswadi EURASIP Journal on Image and Video Processing 2011 2011 14 s EURASIP Journal on Image and Video Processing http content 2011 1 14 RESEARCH Open Access Efficient scan mask techniques for connected components labeling algorithm Phaisarn Sutheebanjard and Wichian Premchaiswadi Abstract Block-based connected components labeling is by far the fastest algorithm to label the connected components in 2D binary images especially when the image size is quite large. This algorithm produces a decision tree that contains 211 leaf nodes with 14 levels for the depth of a tree and an average depth of . This article attempts to provide a faster method for connected components labeling. We propose two new scan masks for connected components labeling namely the pixel-based scan mask and the block-based scan mask. In the final stage the block-based scan mask is transformed to a near-optimal decision tree. We conducted comparative experiments using different sources of images for examining the performance of the proposed method against the existing methods. We also performed an average tree depth analysis and tree balance analysis to consolidate the performance improvement over the existing methods. Most significantly the proposed method produces a decision tree containing 86 leaf nodes with 12 levels for the depth of a tree and an average depth of resulting in faster execution time especially when the foreground density is equal to or greater than the background density of the images. Keywords connected components image processing labeling algorithm linear time algorithm pattern recognition. 1. Introduction Applying connected components labeling in a binary image is of crucial importance in image processing image recognition and computer vision tasks. Labeling operations involve the entire gamut of finding connected components in an image by assigning a unique label to all points in the same component. There are many
