In this paper, an approach based on lacunarity to locate address blocks in postal envelopes is proposed. After computing the lacunarity of a postal envelope image, a non-linear transformation is applied on it. A thresholding technique is then used to generate evidences. Finally, a region growing is applied to reconstruct semantic objects like stamps, postmarks, and address blocks. Very little a priori knowledge of the envelope images is required. By using the lacunarity for several ranges of neighbor window sizes r onto 200 postal envelope images, the proposed approach reached a success rate over than 97% on average. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Facon, J., Menoti, D., & De Albuquerque Araújo, A. (2005). Lacunarity as a texture measure for address block segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3773 LNCS, pp. 112–119). https://doi.org/10.1007/11578079_12
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