0000000001036787

AUTHOR

Shi-lin Wang

showing 2 related works from this author

A Comparative Study on Fuzzy-Clustering-Based Lip Region Segmentation Methods

2011

As the first step of many lip-reading or visual speaker authentication systems, lip region segmentation is of vital importance. And fuzzy clustering based methods have been widely used in lip segmentation. In this paper, four fuzzy clustering based lip segmentation methods have been elaborated with their underlying rationale. Experiments have been carried out evaluate their performance comparatively. From the experimental results, SFCM has the best efficiency and FCMST has the best segmentation accuracy.

AuthenticationFuzzy clusteringComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionstomatognathic diseasesComputingMethodologies_PATTERNRECOGNITIONstomatognathic systemSegmentationArtificial intelligencebusinessSpatial analysisTemporal information
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Sequential Lip Region Segmentation Using Fuzzy Clustering with Spatial and Temporal Information

2012

For many visual speech recognition and visual speaker authentication systems, lip region extraction is of vital important. In order to segment the lip region accurately and robustly from a lip sequence, a new fuzzy-clustering based algorithm is proposed. In the proposed method, a new dissimilarity measure is introduced to take all the color, spatial and temporal information into consideration. An iterative optimization method is employed to derive the optimal lip region membership map and the final segmentation result. From the experimental results, it is observed that the proposed algorithm can provide superior results compared with other traditional methods.

AuthenticationSequenceFuzzy clusteringComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognitionMeasure (mathematics)ComputingMethodologies_PATTERNRECOGNITIONSegmentationArtificial intelligencebusinessTemporal information
researchProduct