In this paper, we propose an approach to automatically locate address blocks in postal envelopes based on fractal dimension. First, the fractal dimension of a postal envelope image is computed. The K-means clustering technique is then used to label pixels as stamps, postmarks, and address blocks.
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.
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