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Yi-Ping Chiu

dblp:142/3940 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Image and video coding
image compression
0.212014
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
0.212014
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
0.212014
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
YearPublicationVenuePosition
2014 A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting
abstract
In 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