Issue No. 12 - December (1999 vol. 21)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.817414
<p><b>Abstract</b>—This paper presents a new compact shape representation for retrieving line-patterns from large databases. The basic idea is to exploit both geometric attributes and structural information to construct a shape histogram. We realize this goal by computing the N-nearest neighbor graph for the lines-segments for each pattern. The edges of the neighborhood graphs are used to gate contributions to a two-dimensional pairwise geometric histogram. Shapes are indexed by searching for the line-pattern that maximizes the cross correlation of the normalized histogram bin-contents. We evaluate the new method on a database containing over 2,500 line-patterns each composed of hundreds of lines.</p>
Image database, line patterns, content-based retrieval, relational representation, geometric features, histogram comparison.
B. Huet and E. R. Hancock, "Line Pattern Retrieval Using Relational Histograms," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 21, no. , pp. 1363-1370, 1999.