Demo Data from EDBT 2026 / reviewers in the wild / expert
Yi-Ping Chiu
dblp:142/3940
· 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
Graphics, computer vision, multimedia, augmented reality and games · 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 coding · 100% | |
| Network and information security
1 paper |
Digital forensics and information hiding · 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 coding
image compression |
0.2 | 1 | 2014 | A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting · IEEE Trans. Image Process. 2014 |
Image and video coding › quantization
vector quantization |
0.2 | 1 | 2014 | A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting · IEEE Trans. Image Process. 2014 |
Digital forensics and information hiding
information hiding |
0.2 | 1 | 2014 | A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting · IEEE Trans. Image Process. 2014 |
Methods — techniques the papers use, named apart from their topics
side match vector quantization · 0.4image inpainting · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image InpaintingabstractIn this paper, we propose a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for the blocks in the leftmost and topmost of the image, each of the other residual blocks in raster-scanning order can be embedded with secret data and compressed simultaneously by SMVQ or image inpainting adaptively according to the current embedding bit. Vector quantization is also utilized for some complex blocks to control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values in the segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme. Chuan Qin 0001, Chin-Chen Chang 0001, Yi-Ping Chiu |
IEEE Trans. Image Process. | 3 |