TY - GEN
T1 - Automatic object extraction in images using embedded labels
AU - Won, Chee Sun
PY - 2008
Y1 - 2008
N2 - To automatically generate images with the same foreground but different backgrounds, a watermark bit (e.g., binary 1 for foreground and 0 for background) can be inserted for each pixel location. Then, the embedded watermark bit can be automatically extracted and the background can be separated from the object. Note that the object extraction can be done successfully only if the watermarked image is intact. However, if the watermarked image goes through some post-processing including JPEG compression and cropping, then the pixel-wise watermark decoding may fail. To overcome this problem, in this paper, a block-wise watermark insertion and a block-wise MAP (maximum a posteriori) watermark decoding are proposed. Experimental results show that the proposed method is more robust that the pixel-wise decoding for various post-processing attacks.
AB - To automatically generate images with the same foreground but different backgrounds, a watermark bit (e.g., binary 1 for foreground and 0 for background) can be inserted for each pixel location. Then, the embedded watermark bit can be automatically extracted and the background can be separated from the object. Note that the object extraction can be done successfully only if the watermarked image is intact. However, if the watermarked image goes through some post-processing including JPEG compression and cropping, then the pixel-wise watermark decoding may fail. To overcome this problem, in this paper, a block-wise watermark insertion and a block-wise MAP (maximum a posteriori) watermark decoding are proposed. Experimental results show that the proposed method is more robust that the pixel-wise decoding for various post-processing attacks.
UR - https://www.scopus.com/pages/publications/52049102012
U2 - 10.1109/CRV.2008.10
DO - 10.1109/CRV.2008.10
M3 - Conference contribution
AN - SCOPUS:52049102012
SN - 9780769531533
T3 - Proceedings of the 5th Canadian Conference on Computer and Robot Vision, CRV 2008
SP - 231
EP - 236
BT - Proceedings of the 5th Canadian Conference on Computer and Robot Vision, CRV 2008
T2 - 5th Canadian Conference on Computer and Robot Vision, CRV 2008
Y2 - 28 May 2008 through 30 May 2008
ER -