Dr. Ilya V. Kurilin Profile

Dr. Ilya V. Kurilin

at SAMSUNG Advanced Institute of Technology

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Author

Publications (6)

Proceedings Article | 21 May 2018 Paper

Computationally efficient and antialiased dual-layer light-field displays

Konstantin Kolchin, Gleb Milyukov, Sergey Turko, Jaeyeol Ryu, Mikhail Popov, Stanislav Shtykov, Ilya Kurilin, Mikhail Rychagov

Proceedings Volume 10676, 106760L (2018) https://doi.org/10.1117/12.2307599

KEYWORDS: LCDs, Spatial light modulators, Image quality, Prototyping, Eye, Cameras, Mobile devices, Virtual reality, Image resolution, Stereoscopic displays

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Proceedings Article | 8 February 2015 Paper

Fast Algorithm for Visibility Enhancement of the Images with Low Local Contrast

Ilya Kurilin, Ilia Safonov, Michael Rychagov, Sergey Zavalishin, Dong Hyeop Han, Sang Ho Kim

Proceedings Volume 9395, 93950B (2015) https://doi.org/10.1117/12.2078975

KEYWORDS: Visibility, Image enhancement, RGB color model, Visualization, Image filtering, Image processing, Linear filtering, Optimization (mathematics), Image contrast enhancement, High dynamic range imaging

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Proceedings Article | 3 February 2014 Paper

High-performance automatic cropping and deskew of multiple objects on scanned images

Ilya Kurilin, Ilia Safonov, Michael Rychagov, Hokeun Lee, Sang Ho Kim

Proceedings Volume 9016, 90160B (2014) https://doi.org/10.1117/12.2037257

KEYWORDS: Image segmentation, Image processing algorithms and systems, Scanners, Image resolution, Image processing, Binary data, Detection and tracking algorithms, Image classification, Image quality, Algorithm development

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Proceedings Article | 4 February 2013 Paper

Generation of PDF with vector symbols from scanned document

Ilya Kurilin, Ilia Safonov, Michael Rychagov, Hokeun Lee, Sang Ho Kim, Donchul Choi

Proceedings Volume 8653, 86530R (2013) https://doi.org/10.1117/12.2000527

KEYWORDS: Raster graphics, Image segmentation, Resolution enhancement technologies, Visualization, Evolutionary algorithms, Corner detection, Image resolution, Electronics, Optical character recognition, Printing

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Proceedings Article | 25 January 2011 Paper

Fast approach for toner saving

Ilia Safonov, Ilya Kurilin, Michael Rychagov, Hokeun Lee, Sangho Kim, Donchul Choi

Proceedings Volume 7866, 786618 (2011) https://doi.org/10.1117/12.872123

KEYWORDS: Raster graphics, Printing, Optical character recognition, Solids, Visualization, Absorbance, 3D printing, Patents, Image quality, Electronics

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Proceedings Article | 19 January 2010 Paper

Descreening of scanned images

Ilya Kurilin, Ilia Safonov, HoKeun Lee, Sang Ho Kim

Proceedings Volume 7528, 75280D (2010) https://doi.org/10.1117/12.838444

KEYWORDS: Halftones, Image filtering, Image processing, RGB color model, Linear filtering, Visualization, Optical filters, High dynamic range imaging, Detection and tracking algorithms, Printing

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Screen or halftone pattern appears on the majority of images printed on electrophotographic and ink-jet printers as well as offset machines. When such halftoned image is scanned, a noisy effect called a Moiré pattern often appears on the image. There are plenty of methods proposed for descreening of images. Common way is adaptive smoothing of scanned images. However the descreening techniques face the following dilemma: deep screen reduction and restoration of contone images leads to blurring of sharp edges of text and other graphics primitives, on the other hand insufficient smoothing keeps screen in halftoned areas. We propose novel descreening algorithm that is primarily intended for preservation of sharpness and contrast of text edges and for restoration contone images from halftone ones accurately. Proposed technique for descreening of scanned images comprises five steps. The first step is decrease of edge transition slope length via local tone mapping with ordering; it is carried out before adaptive smoothing, and it allows better preservation of edges. Adaptive low-pass filter applies simplified idea of Non-Local Means filter for area classification; similarity is calculated between central block of window and different adjacent block that is selected randomly. If similarity is high then current pixel relates to flat region, otherwise pixel relates to edge region. For prevention of edges blurring, flat regions are smoothed stronger than edge regions. By random selection of blocks we avoid the computational overhead related to excessive directional edge detection. Final three stages include additional decrease of edge transition slope length using local tone mapping, increase of local contrast via modified unsharp mask filter, that uses bilateral filter with special edge-stop function for modest smoothing of edges, and global contrast stretching. These stages are intended to compensate decreasing of sharpness and contrast due to low-pass filtering, it allows to enhance visual quality of scanned image. For parameters adjusting for different scanning resolutions and comparison with existing techniques test target and criteria were proposed. Also the quality of proposed approach is evaluated by surveying observer's opinions. According to obtained outcomes the proposed algorithm demonstrates good descreening capabilities.

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