H
Hiroki Kanno
Researcher at Toshiba
Publications - 31
Citations - 443
Hiroki Kanno is an academic researcher from Toshiba. The author has contributed to research in topics: Image processing & Color image. The author has an hindex of 14, co-authored 31 publications receiving 443 citations.
Papers
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Patent
Apparatus for processing image data among media having different image output sizes
Gururaj Rao,Hiroki Kanno +1 more
TL;DR: In this article, the authors detect the features of the document, such as the top, bottom, left and right margins, the character space, the line space, word space, column space, size and coordinates of each character, and the like.
Patent
System and method for defining characteristic data of a scanned document
TL;DR: In this article, a system and a method for providing characteristic data associated with a scanned document is provided. The method includes analyzing a bitmapped image file of a document, determining at least one characteristic data of the document, and linking the characteristic data to the image file, wherein the document is useable by a document management system to identify the document in a search.
Patent
Image processing apparatus with improved dithering scheme
Hiroki Kanno,Hitoshi Yoneda +1 more
TL;DR: In this paper, the maximum density difference of an image within a predetermined range is calculated as a feature amount, and a quantization error of pixels around a pixel of interest is calculated, and then, a correction amount is calculated by proportionally distributing the quantization errors in accordance with the feature amount calculated by a feature amounts calculator.
Patent
Image processor and image processing system
Hiroki Kanno,Gaku Takano +1 more
TL;DR: In this paper, an image processor includes an image input unit for reading and inputting an image of a document, an image output unit for outputting the image processed by the image processing unit.
Patent
Apparatus for image processing
Sunao Tabata,Hiroki Kanno +1 more
TL;DR: In this paper, a first compressing section which compresses each block of an image into first compressed data, a first code converting section which converts the first compressed dataset into second compressed dataset, a second code converting segmentation section which transforms the second dataset into third dataset and a decoding section which decodes the third dataset.