scispace - formally typeset
D

Dan S. Bloomberg

Researcher at Xerox

Publications -  78
Citations -  4590

Dan S. Bloomberg is an academic researcher from Xerox. The author has contributed to research in topics: Binary image & Image processing. The author has an hindex of 34, co-authored 78 publications receiving 4589 citations.

Papers
More filters
Patent

Performing document image management tasks using an iconic image having embedded encoded information

TL;DR: In this article, an encoding operation encodes the data unobtrusively in the form of rectangular blocks that have a foreground color and size dimensions proportional to the iconic image so that when placed in the iconic images in horizontal lines, the blocks appear to a viewer to be representative of the text portion of the original image that they replace.
Patent

Embedding encoded information in an iconic version of a text image

TL;DR: An encoding operation encodes binary data that is then embedded in an iconic, or size-reduced, version of an original text image, in a position in the iconic image that replaces a text portion in the original text text as discussed by the authors.
Patent

Hardcopy lossless data storage and communications for electronic document processing systems

TL;DR: Machine readable electronic domain definitions of hardcopy documents and/or of part or all of the transforms that are performed to produce and reproduce such hardcopies documents are encoded in codes that are printed on such documents, thereby permitting the electronic domain descriptions of such documents and or such transforms to be recovered more robustly and reliably when the information carried by such documents is transformed from the hardcopy domain to electronic domain this article.
Patent

Adaptive scaling for decoding spatially periodic self-clocking glyph shape codes

TL;DR: Weighted and unweighted convolution filtering processes are provided for decoding bitmap image space representations of self-clocking glyph shape codes and for tracking the number and locations of the ambiquities or "errors" that are encountered during the decoding as mentioned in this paper.
BookDOI

Mathematical morphology and its applications to image and signal processing

TL;DR: A Morphological View on Traditional Signal Processing and Morphological Scale-Space Operators: An Algebraic Framework and New Insight on Digital Topology G.T. Popov.