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Efficient component labeling of images of arbitrary dimension represented by linear bintrees

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2 Author(s)
H. Samet ; Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA ; M. Tamminen

An algorithm is presented to perform connected-component labeling of images of arbitrary dimension that are represented by a linear bintree. The bintree is a generalization of the quadtree data structure that enables dealing with images of arbitrary dimension. The linear bintree is a pointerless representation. The algorithm uses an active border which is represented by linked lists instead of arrays. This results in a significant reduction in the space requirements, thereby making it feasible to process three- and higher-dimensional images. Analysis of the execution time of the algorithm shows almost linear behavior with respect to the number of leaf nodes in the image, and empirical tests are in agreement. The algorithm can be modified easily to compute a (d-1)-dimensional boundary measure (e.g. perimeter in two dimensions and surface area in three dimensions) with linear performance

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:10 ,  Issue: 4 )