Abstract book (pdf) - ICPR 2010

coefficients for embedding the watermark, three different aspects, imperceptibility, security, and bit rate increase, have
been considered. These performance factors are adjusted by defining three priority matrices. In addition, a content based
key is proposed in order to overcome the collusion attack. The flexibility of our method to provide desired characteristic
can be expressed as another advantage.
09:00-11:10, Paper WeAT8.60
Lip Segmentation using Level Set Method: Fusing Landmark Edge Distance and Image Information
Banimahd, Seyed Reza, Sahand Univ. of Tech.
Ebrahimnezhad, Hossein, Sahand Univ. of Tech.
Lip segmentation is an essential step in audio-visual processing systems. In this paper, we incorporate the color and edge
information in level set formulation, for extraction of lip contour. We build two initiative auxiliary images by mixing of
different color spaces, to extract the landmark edges for upper and lower part of lip. The performance of this approach on
VidTIMIT databases is tasted and accuracy of 91.2% is reached.
09:00-11:10, Paper WeAT8.61
Adaptive Color Independent Components based SIFT Descriptors for Image Classification
Ai, Danni, Ritsumeikan Univ.
Han, Xian-Hua, Ritsumeikan Univ.
Ruan, Xiang, Omron corparation
Chen, Yen-Wei, Ritsumeikan Univ.
This paper proposes an adaptive color independent components based SIFT descriptor (termed CIC-SIFT) for image classification.
Our motivation is to seek an adaptive and efficient color space for color SIFT feature extraction. Our work has
two key contributions. First, based on independent component analysis (ICA), an adaptive and efficient color space is
proposed for color image representation. Second, in this ICA-based color space, a discriminative CIC-SIFT descriptor is
calculated for image classification. The experiment results indicate that (1) contrast between objects and background can
be enhanced on the ICA-based color space and (2) the CIC-SIFT descriptor outperforms other conventional color SIFT
descriptors on image classification.
WeAT9 Lower Foyer
Bioinformatics and Biomedical Applications Poster Session
Session chair: Unay, Devrim (Bahcesehir Univ.)
09:00-11:10, Paper WeAT9.1
Joint Registration and Segmentation of Histological Volume Data by Diffusion-Based Label Adaption
Bollenbeck, Felix, Fraunhofer Inst. for Factory Operation and Automation
Seiffert, Udo, Fraunhofer IFF Magdeburg
Three-dimensional serial section imaging delivers high spatial resolution and histological detail, which facilitates analysis
of differentiation and development by exact labelling of tissues and cells, unknown to other 3-D imaging modalities. We
propose an algorithm for interleaved reconstruction and segmentation of tissues in serial section volumes by diffusionbased
registration and adaption of two-dimensional reference labellings. Iterative refinement of the global image congruence
and local deformation of labellings delivers an efficient algorithm for processing of large volume data-sets. The
benefits of the approach are shown by means of reconstruction and segmentation of giga-voxel serial section volumes of
plant specimen.
09:00-11:10, Paper WeAT9.2
The Use of Genetic Programming for Learning 3D Craniofacial Shape Quantification
Atmosukarto, Indriyati, Univ. of Washington
Shapiro, Linda,
Heike, Carrie, Seattle Children’s Hospital, Craniofacial Center
Craniofacial disorders commonly result in various head shape dysmorphologies. The goal of this work is to quantify the
various 3D shape variations that manifest in the different facial abnormalities in individuals with a craniofacial disorder
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