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Automatic Text Extraction for Content-Based Image Indexing

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3056))

Abstract

This paper proposes an approach for automatic text extraction method using neural networks. Automatic text extraction is a crucial stage for multimedia data mining. We present an artificial neural network (ANNs)-based approach for text extraction in complex images, which uses a combined method of ANNs and non-negative matrix factorization (NMF)-based filtering. An automatically constructed ANN-based classifier can increase recall rates for complex images with small amount of user intervention. NMF-based filtering enhances the precision rate without affecting overall performance. As a result, a combination of two learning mechanism leads to not only robust but also efficient text extraction.

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References

  1. Lienhart, R., Stuber, F.: Automatic Text Recognition In Digital Videos. In: SPIEThe International Society for Optical Engineering, pp. 180–188 (1996)

    Google Scholar 

  2. Li, H., Doerman, D., Kia, O.: Automatic Text Detection and Tracking in Digital Video. IEEE Transactions on Image Processing 9(1), 147–156 (2000)

    Article  Google Scholar 

  3. Zhong, Y., Zhang, H., Jain, A.K.: Automatic Caption Extraction in Compressed Video. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(4), 385–392 (2000)

    Article  Google Scholar 

  4. Kim, E.Y., Jung, K., Jeong, K.Y., Kim, H.J.: Automatic Text Region Extraction Using Cluster-based Templates. In: International Conference on Advances in Pattern Recognition and Digital Techniques, pp. 418–421 (2000)

    Google Scholar 

  5. Jeong, K.Y., Jung, K., Kim, E.Y., Kim, H.J.: Neural Network-based Text Location for News Video Indexing. In: Proceedings of International Conference of Image Processing, vol. 3, pp. 319–323 (1999)

    Google Scholar 

  6. Wu, V., Manmatha, R., Riseman, E.M.: TextFinder: An Automatic System to Detect and Recognize Text in Images. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(11), 1224–1229 (1999)

    Article  Google Scholar 

  7. Jung, K.: Neural Network-based Text Location in Color Images. Pattern Recognition Letters 22(14), 1503–1515 (2001)

    Article  MATH  Google Scholar 

  8. Gargi, U., Antani, S., Kasturi, R.: Indexing Text Events in Digital Video Database. In: International Conference on Pattern Recognition, pp. 1481–1483 (1998)

    Google Scholar 

  9. Sung, K.K., Poggio, T.: Example-based Learning for View-based Human Face Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(1), 39–51 (1998)

    Article  Google Scholar 

  10. Cheng, Y.: Mean Shift, Mode Seeking, and Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(8), 790–799 (1995)

    Article  Google Scholar 

  11. Lee, D.D., Seung, H.S.: Learning the Parts of Objects by Non-Negative Matrix Factorization. Nature 401, 788–791 (1999)

    Article  Google Scholar 

  12. Lee, D.D., Seung, H.S.: Algorithms for non-negative matrix factorization. Advances in Neural Information Processing Systems 13, 556–562 (2001)

    Google Scholar 

  13. http://www.informatik.uni-mannheim.de/informatik/pi4/projects/MoCA/ProjecttextSegmentationAndRecognition.html

  14. Kim, K.I., Jung, K.: Texture-based Approach for Text Detection in Images using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1631–1639 (2003)

    Article  MathSciNet  Google Scholar 

  15. Jung, K., Kim, K.I.: a.A.K. Jain, Text Information Extraction in Images: A Survey. International Journal of Pattern Recognition (to be published)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Jung, K., Kim, E.Y. (2004). Automatic Text Extraction for Content-Based Image Indexing. In: Dai, H., Srikant, R., Zhang, C. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2004. Lecture Notes in Computer Science(), vol 3056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24775-3_60

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  • DOI: https://doi.org/10.1007/978-3-540-24775-3_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22064-0

  • Online ISBN: 978-3-540-24775-3

  • eBook Packages: Springer Book Archive

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