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Vladimir Bereishik

dblp:46/2900 · DBLP profile ↗
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5ranked-venue papers
0as first author
0since 2021 · last 2002
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4Graphics, computer vision, multimedia, augmented reality and games · 3Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 50% Visual content generation and editing · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Parallel and multicore computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing
document image analysis
0.011993
A system for automatic vectorization and interpretation of map-drawings · ICCV 1993
Visual content generation and editing
image vectorization
0.011993
A system for automatic vectorization and interpretation of map-drawings · ICCV 1993
Parallel and multicore computing
pipelined processing
0.011993
A system for automatic vectorization and interpretation of map-drawings · ICCV 1993

Methods — techniques the papers use, named apart from their topics

transputer chain · 0.0pipeline-oriented scheme · 0.0
YearPublicationVenuePosition
2002 Reconstruction of 3D Object Models from Vectorised Engineering Drawings
Sergey Ablameyko 0001, Vladimir Bereishik, Alexander Gorelik, Sergev Medvedev
Pattern Anal. Appl.2
1998 A system for automatic recognition of engineering drawing entities
abstract
The paper describes the VEDI (Vectorization of Engineering Drawing Images) system developed for automatic recognition of main engineering drawing (ED) entities. The main principles of ED interpretation are introduced and the algorithms to recognize main ED entities are briefly described. In conclusion, some technical parameters and experimental results of the system performance are given.
Sergey Ablameyko 0001, Vladimir Bereishik, Oleg Frantskevich, Maria Homenko, Nadeshda Paramonova
ICPR2
1997 Algorithms for Recognition of the Main Engineering Drawing Entities
abstract
The paper introduces the main principles of automatic interpretation of engineering drawing images. The technology of ED interpretation is proposed based on the introduced principles. The algorithms for automatic recognition of the main ED entities: line types, circular arcs, blocks, crosshatched areas and dimensions are proposed. They have been verified experimentally in the whole ED interpretation technology and show good results.
Sergey Ablameyko 0001, Vladimir Bereishik, Oleg Frantskevich, Maria Homenko, Nadeshda Paramonova
ICDAR2
1994 Vectorization and Representation of Large-Size 2-D Line-Drawing Images
Sergey Ablameyko 0001, Vladimir Bereishik, Nadeshda Paramonova, Angelo Marcelli, Seiji Ishikawa, Kiyoshi Kato
J. Vis. Commun. Image Represent.2
1993 A system for automatic vectorization and interpretation of map-drawings
abstract
The authors describe a system for automatic interpretation of map-drawings. To vectorize large-size 2-D line-drawing images, an effective pipeline-oriented scheme and special techniques have been developed on the basis of economic image representation. This allows processing large-size binary images on a personal computer and obtaining satisfactory time characteristics. This approach can be easily realized in a pipelined architecture using a simple transputer chain. The document object recognition techniques are described.>
Sergey Ablameyko 0001, Vladimir Bereishik, Oleg Frantskevich, Maria Homenko, E. Melnik, Oleg Okun, Nadeshda Paramonova
ICCV2