Abstract
In this paper, the K-means algorithm for information extraction in the form of text from complex video images using 2D wavelet is presented. Haar wavelet and K-means algorithm-based simple hybrid approach are proposed in this paper. Haar wavelet is used to efficiently convert grayscale image to edge image. K-means algorithm is used for the information localization and segmentation process to split the background pixels from the text images. Large non-text background interrupts to extract the text information from any video images, so that non-text background can be identified and eliminated from the text images with the help of the hybrid approach. This algorithm is evaluated on the complex background video frames. The recall rate and the precision rate are obtained 99.01 and 95.75% of the proposed algorithm in video images.
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Saxena, D., Kumar, A. (2021). K-Means Algorithm-Based Text Extraction from Complex Video Images Using 2D Wavelet. In: Satapathy, S.C., Bhateja, V., Favorskaya, M.N., Adilakshmi, T. (eds) Smart Computing Techniques and Applications. Smart Innovation, Systems and Technologies, vol 224. Springer, Singapore. https://doi.org/10.1007/978-981-16-1502-3_23
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DOI: https://doi.org/10.1007/978-981-16-1502-3_23
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