An accurate tongue tissue strain synthesis using pseudo-wavelet reconstruction-based tagline detection
Author(s) -
Xiaohui Yuan,
Cengizhan Öztürk,
Gloria ChiFishman
Publication year - 2007
Publication title -
proceedings of spie, the international society for optical engineering/proceedings of spie
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.192
H-Index - 176
eISSN - 1996-756X
pISSN - 0277-786X
DOI - 10.1117/12.710402
Subject(s) - wavelet , artificial intelligence , computer science , computer vision , thresholding , robustness (evolution) , wavelet transform , noise (video) , pattern recognition (psychology) , computer graphics (images) , image (mathematics) , chemistry , biochemistry , gene
This paper describe our work on tagline detection and tissue strain synthesis. The tagline detection method extends our previous work16 using pseudo-wavelet reconstruction. The novelty in tagline detection is that we integrated an active contour model and successfully improved the detection and indexing performance. Using pseudo-wavelet reconstruction-based method, prominent wavelet coefficients were retained while others were eliminated. Taglines were then extracted from the reconstructed images using thresholding. Due to noise and artifacts, a tagline can be broken into segments. We employed an active contour model that tracks the most likely segments and bridges them. Experiments demonstrated that our method extracts taglines automatically with greater robustness. Tissue strain was also reconstructed using extracted taglines.
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