Two Access Methods Using Compact Binary Trees
IEEE Transactions on Software Engineering
The Interpolation-Based Bintree and encoding of binary images
CVGIP: Graphical Models and Image Processing
Finding neighbors of equal size in linear quadtrees and octrees in constant time
CVGIP: Image Understanding
A fast search algorithm on modified S-trees
Pattern Recognition Letters
Communications of the ACM
Interpolation search—a log logN search
Communications of the ACM
On a Method of Binary-Picture Representation and Its Application to Data Compression
IEEE Transactions on Pattern Analysis and Machine Intelligence
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The interpolation-based bintree is a storage-saving encoding scheme for representing binary images. It represents the image by using a sequence of increasing positive integers, called bincodes. In this paper, an efficient algorithm for solving the problem of neighbor finding on bincodes is presented. The time complexity of the algorithm is O (n log log n), where n is the number of the bincodes. In addition, experimental results are included to confirm the theoretical analysis. These experimental values show that our algorithm is faster than the previous best known results (Huang and Chung, 1995a, b). Furthermore, by using the conversion algorithms, we can apply our algorithm for the neighbor-finding problem on images represented by other representations such as the locational codes, the DF-expression, the S-tree, and the Morton codes to achieve better performance.