Demo Data from VLDB 2026 / reviewers in the wild / expert
Ilya Blayvas
dblp:00/5269
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing › image segmentation
image binarization |
0.0 | 1 | 2001 | Efficient Computation of Adaptive Threshold Surfaces for Image Binarization · CVPR (1) 2001 |
Image and video processing
image segmentation |
0.0 | 1 | 2001 | Efficient Computation of Adaptive Threshold Surfaces for Image Binarization · CVPR (1) 2001 |
Image and video processing › image segmentation
thresholding |
0.0 | 1 | 2001 | Efficient Computation of Adaptive Threshold Surfaces for Image Binarization · CVPR (1) 2001 |
Methods — techniques the papers use, named apart from their topics
successive overrelaxation · 0.0multiresolution approximation · 0.0interpolation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | Efficient computation of adaptive threshold surfaces for image binarization
Ilya Blayvas, Alfred M. Bruckstein, Ron Kimmel |
Pattern Recognit. | 1 |
| 2001 | Efficient Computation of Adaptive Threshold Surfaces for Image BinarizationabstractThe problem of binarization of gray level images acquired under nonuniform illumination is reconsidered. Yanowitz and Bruckstein (1989) proposed to use an adaptive threshold surface, determined by interpolation of the image gray levels at points where the image gradient is high. The rationale is that a high image gradient indicates probable object edges, and there the image values are between the object and background gray levels. The threshold surface was determined by successive overrelaxation as the solution of the Laplace equation. This work proposes a different method to determine an adaptive threshold surface. In this new method, inspired by multiresolution approximation, the threshold surface is constructed with considerably lower computational complexity and is smooth, yielding faster image binarizations and better visual performance. Ilya Blayvas, Alfred M. Bruckstein, Ron Kimmel |
CVPR (1) | 1 |