Demo Data from VLDB 2026 / reviewers in the wild / expert
Keisuke Matsuyama
dblp:67/5213
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Electronic design automation · 100% | |
| 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 |
|---|---|---|---|---|
Electronic design automation › hardware test
defect detection |
0.2 | 1 | 2014 | Pipelining FPPGA-based defect detction in FPDs (abstract only) · FPGA 2014 |
Image and video processing
edge detection |
0.1 | 1 | 2014 | Pipelining FPPGA-based defect detction in FPDs (abstract only) · FPGA 2014 |
Image and video processing › image segmentation
image binarization |
0.1 | 1 | 2014 | Pipelining FPPGA-based defect detction in FPDs (abstract only) · FPGA 2014 |
Methods — techniques the papers use, named apart from their topics
pipelining · 0.4line buffer · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Pipelining FPPGA-based defect detction in FPDs (abstract only)abstractThe real-time detection of defects in Flat-Panel Displays (FPDs) is very important during the production stages. This paper describes the manner in which defects induced by bubbles are detected as fast as possible by using 4-stage image processing pipelines with 3-line buffers on a Field-Programmable Gate Array (FPGA). The image processing consists of reading a Time Delay Integration (TDI) image, Laplacian filtering, binarization, and labeling. TDI is applied to the initial image of the FPD to reduce noises induced when taking the FPD images. Laplacian filtering and binarization are used to detect the edges in the image, and labeling is used to number the objects in the image for defect detection. In the 4-stage pipelining, the first stage reads the TDI image from the Block Random Access Memory (BRAM), the second stage implements Laplacian filtering and binarization, the third stage implements labeling, and the final stage revises the labels and writes them into the BRAM. The target pixel and its eight surrounding neighbors are required during Laplacian filtering, and four neighbors are necessary during labeling. Thus, three line registers (3-line buffer) are used as a general pipeline register between two neighboring stages in our system. The pipelining system accesses these 3-line buffers and runs four image processing steps in parallel. Therefore, the system uses four different addresses to access the BRAM and the 3-line buffers. Further, to facilitate performance comparison, we implemented sequential image processing systems with 3-line buffers on FPGA and CPU software. The experiments reveal that Laplacian filtering, binarization, and labeling for FPD defect detection can be executed in less than 1 ms by using four-stage pipelining on an FPGA, which is 3.62 times faster than the sequential system and 158.7 times faster than the CPU software. The pipelining system is 28% larger as compared to the sequential system in terms of the size of the LUTs. Lin Meng 0001, Keisuke Matsuyama, Naoto Nojiri, Tomonori Izumi, Katsuhiro Yamazaki |
FPGA | 2 |