Abstract
This chapter presents a method for caption text detection. The proposed method will be included in a generic indexing system dealing with other semantic concepts which are to be automatically detected as well. To have a coherent detection system, the various object detection algorithms use a common image description, a hierarchical region-based image model. The proposed method takes advantage of texture and geometric features to detect the caption text. Texture features are estimated using wavelet analysis and mainly applied for text candidate spotting. In turn, text characteristics verification relies on geometric features, which are estimated exploiting the region-based image model. Analysis of the region hierarchy provides the final caption text objects. The final step of consistency analysis for output is performed by a binarization algorithm that robustly estimates the thresholds on the caption text area of support.
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Notes
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All images used in this chapter belong to TVC, Television de Catalunya, and are copyright protected. These key-frames have been provided by TVC with the only goal of research under the framework of the i3media project.
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Acknowledgments
This work was partially founded by the Catalan Broadcasting Corporation (CCMA) and Mediapro through the Spanish project CENIT-2007-1012 i3media and TEC2007-66858/TCM PROVEC of the Spanish Government.
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Leon, M., Vilaplana, V., Gasull, A., Marques, F. (2013). Region-Based Caption Text Extraction. In: Adami, N., Cavallaro, A., Leonardi, R., Migliorati, P. (eds) Analysis, Retrieval and Delivery of Multimedia Content. Lecture Notes in Electrical Engineering, vol 158. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3831-1_2
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DOI: https://doi.org/10.1007/978-1-4614-3831-1_2
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