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- W3036705076 abstract "The images embedded with text contain information and therefore it is important to identify and extract text. Extracting text in a blurred image is a challenging task due to movement and defocus, whereas it is an easy task in the nonblurred image. In this paper, text identification from non-blur and blur images is done using an Otsu method and region of interest (ROI) and text are extracted using a convolution neural network (CNN). The evaluation results show 98.1% accuracy for non-blurred images and 96% accuracy for blurred images. The text is extracted and identified with efficient accuracies than the existing methods." @default.
- W3036705076 created "2020-06-25" @default.
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- W3036705076 date "2020-05-01" @default.
- W3036705076 modified "2023-09-26" @default.
- W3036705076 title "Identification and Extraction of Text in Non- Blurred and Blurred Image Sequences" @default.
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- W3036705076 doi "https://doi.org/10.1109/iciccs48265.2020.9120884" @default.
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