Scene text extraction in complex images

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Abstract

Text extraction and recognition from still and moving images have many important applications. But, when a source image is an ordinary natural scene, text extraction becomes very complicated and difficult. In this paper, we suggest text extraction methods based on color and gray information. The method using the color image is processed by color reduction, color clustering, and text region extraction and verifications. The method using the gray-level image is processed by edge detection, long line removal, repetitive run-length smearing (RLS), and text region extraction and verifications. Combining two approaches improves the extraction accuracies both in simple and in complex images. Also, estimating skew and perspective of the extracted text regions are considered.

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Byun, H. R., Roh, M. C., Kim, K. C., Choi, Y. W., & Lee, S. W. (2002). Scene text extraction in complex images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2423, pp. 329–340). Springer Verlag. https://doi.org/10.1007/3-540-45869-7_38

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