Title :
Automatic Object Extraction in Images using Embedded Labels
Author_Institution :
Dept of Electron. Eng., Dongguk Univ., Seoul
Abstract :
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.
Keywords :
data compression; data encapsulation; feature extraction; image coding; image recognition; maximum likelihood decoding; watermarking; JPEG compression; JPEG cropping; automatic object extraction; block-wise MAP watermark decoding; block-wise watermark insertion; embedded label; image watermarking; maximum a posteriori; pixel-wise watermark decoding; post-processing attack; Additive noise; Bayesian methods; Decoding; Humans; Image coding; Image generation; Image segmentation; Pixel; Transform coding; Watermarking; Object segmentation; QIM; background replacement;
Conference_Titel :
Computer and Robot Vision, 2008. CRV '08. Canadian Conference on
Conference_Location :
Windsor, Ont.
Print_ISBN :
978-0-7695-3153-3
DOI :
10.1109/CRV.2008.10