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Document Image Processing for Scanning and Printing [electronic resource] / by Ilia V. Safonov, Ilya V. Kurilin, Michael N. Rychagov, Ekaterina V. Tolstaya.

By: Safonov, Ilia V [author.].
Contributor(s): Kurilin, Ilya V [author.] | Rychagov, Michael N [author.] | Tolstaya, Ekaterina V [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Signals and Communication Technology: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019.Description: XVIII, 305 p. 249 illus., 165 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030053420.Subject(s): Signal processing | Computer vision | Signal, Speech and Image Processing | Computer VisionAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
Distortion-free Image Capturing at Scanning/Copying of the Bound Documents -- Image restoration of compact bound documents -- Intellectual Two-sided card copy -- Automatic cropping and deskew of multiple objects -- Mobile image/document enhancement -- Bottom-up Document Segmentation Method Based on Textural Features -- Document image classification on the basis of layout information -- Image/ Poster stitching -- Fast JPEG rate control -- Generation of PDF with vector symbols from scanned document -- Transformation of screenshot to metafile -- Embedding hidden data into hardcopy -- Embedding hidden data into hardcopy -- Micro-printing -- Creation of micro-pictures for secured printing -- Fast approach for toner saving -- Integraphic Printing.
In: Springer Nature eBookSummary: This book continues first one of the same authors “Adaptive Image Processing Algorithms for Printing” and presents methods and software solutions for copying and scanning various types of documents by conventional office equipment, offering techniques for correction of distortions and enhancement of scanned documents; techniques for automatic cropping and de-skew; approaches for segmentation of text and picture regions; documents classifiers; approach for vectorization of symbols by approximation of their contour by curves; methods for optimal compression of scanned documents, algorithm for stitching parts of large originals; copy-protection methods by microprinting and embedding of hidden information to hardcopy; algorithmic approach for toner saving. In addition, method for integral printing is considered. Described techniques operate in automatic mode thanks to machine learning or ingenious heuristics. Most the techniques presented have a low computational complexity and memory consumption due to they were designed for firmware of embedded systems or software drivers. The book reflects the authors’ practical experience in algorithm development for industrial R&D. .
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Distortion-free Image Capturing at Scanning/Copying of the Bound Documents -- Image restoration of compact bound documents -- Intellectual Two-sided card copy -- Automatic cropping and deskew of multiple objects -- Mobile image/document enhancement -- Bottom-up Document Segmentation Method Based on Textural Features -- Document image classification on the basis of layout information -- Image/ Poster stitching -- Fast JPEG rate control -- Generation of PDF with vector symbols from scanned document -- Transformation of screenshot to metafile -- Embedding hidden data into hardcopy -- Embedding hidden data into hardcopy -- Micro-printing -- Creation of micro-pictures for secured printing -- Fast approach for toner saving -- Integraphic Printing.

This book continues first one of the same authors “Adaptive Image Processing Algorithms for Printing” and presents methods and software solutions for copying and scanning various types of documents by conventional office equipment, offering techniques for correction of distortions and enhancement of scanned documents; techniques for automatic cropping and de-skew; approaches for segmentation of text and picture regions; documents classifiers; approach for vectorization of symbols by approximation of their contour by curves; methods for optimal compression of scanned documents, algorithm for stitching parts of large originals; copy-protection methods by microprinting and embedding of hidden information to hardcopy; algorithmic approach for toner saving. In addition, method for integral printing is considered. Described techniques operate in automatic mode thanks to machine learning or ingenious heuristics. Most the techniques presented have a low computational complexity and memory consumption due to they were designed for firmware of embedded systems or software drivers. The book reflects the authors’ practical experience in algorithm development for industrial R&D. .

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