Neural Networks - Special issue: Emotion and brain
Robust lip region segmentation for lip images with complex background
Pattern Recognition
Robust feature detection for facial expression recognition
Journal on Image and Video Processing
Multimodal person authentication using speech, face and visual speech
Computer Vision and Image Understanding
Facial feature localization based on an improved active shape model
Information Sciences: an International Journal
Color PCA eigenimages and their application to compression and watermarking
Image and Vision Computing
Human Lips as Emerging Biometrics Modality
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Real time face and mouth recognition using radial basis function neural networks
Expert Systems with Applications: An International Journal
Lips Recognition for Biometrics
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
LipMouse: novel multimodal human-computer interaction interface
SIGGRAPH '09: Posters
Combining region and edge information to extract fish oocytes in histological images
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Lip contour extraction for language learning in VEC3D
Machine Vision and Applications
Adjusted pixel features for robust facial component classification
Image and Vision Computing
Lip contour extraction using level set curve evolution with shape constraint
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
An intelligent multimedia E-learning system for pronunciations
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
PC-based asymmetry analyzer for facial palsy study in uncontrolled environment: A preliminary study
Computer Methods and Programs in Biomedicine
Intelligent wheelchair multi-modal human-machine interfaces in lip contour extraction based on PMM
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Fovea intensity comparison code for person identification and verification
Engineering Applications of Artificial Intelligence
Combining edge detection and region segmentation for lip contour extraction
AMDO'10 Proceedings of the 6th international conference on Articulated motion and deformable objects
Controlling computer by lip gestures employing neural networks
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Locating facial landmarks by support vector machine-based active shape model
International Journal of Intelligent Systems Technologies and Applications
Artificial immune multi-objective SAR image segmentation with fused complementary features
Information Sciences: an International Journal
ICECS'05 Proceedings of the 4th WSEAS international conference on Electronics, control and signal processing
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Extended fitting methods of active shape model for the location of facial feature points
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
A local region based approach to lip tracking
Pattern Recognition
Intelligent video and audio applications for learning enhancement
Journal of Intelligent Information Systems
Segmentation of color images using a linguistic 2-tuples model
Information Sciences: an International Journal
Natural Computing: an international journal
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Recently, lip image analysis has received much attention because its visual information is shown to provide improvement for speech recognition and speaker authentication. Lip image segmentation plays an important role in lip image analysis. In this paper, a new fuzzy clustering method for lip image segmentation is presented. This clustering method takes both the color information and the spatial distance into account while most of the current clustering methods only deal with the former. In this method, a new dissimilarity measure, which integrates the color dissimilarity and the spatial distance in terms of an elliptic shape function, is introduced. Because of the presence of the elliptic shape function, the new measure is able to differentiate the pixels having similar color information but located in different regions. A new iterative algorithm for the determination of the membership and centroid for each class is derived, which is shown to provide good differentiation between the lip region and the nonlip region. Experimental results show that the new algorithm yields better membership distribution and lip shape than the standard fuzzy c-means algorithm and four other methods investigated in the paper.