Automatic lip contour extraction using pixel-based segmentation and piece-wise polynomial fitting
| Autor: | Debadatta Pati, Salam Nandakishor, Sukesh Kumar Das |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Polynomial
Pixel Computer science business.industry 020206 networking & telecommunications Pattern recognition 02 engineering and technology Image segmentation Thresholding stomatognathic diseases Region of interest Computer Science::Computer Vision and Pattern Recognition Active shape model 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Segmentation Artificial intelligence Cluster analysis business |
| Zdroj: | 2017 14th IEEE India Council International Conference (INDICON). |
| DOI: | 10.1109/indicon.2017.8487538 |
| Popis: | This work presents automatic lip contour extraction using pixel-based segmentation and piece-wise polynomial fitting. In the first stage, the region of interest (ROI) i.e. mouth region is extracted by binary classification based on color ratio thresholding followed by centrally located large connected region detection. k-means clustering is applied to green plane to get upper lip area. The lower lip area is obtained by using binary k-means clustering to the weighted plane. The combined lip area is further processed to detect the centrally located big connected region. Robert filtering followed by similar neighbour traversing are employed to estimate the lip contour. A smoothed upper and lower contours are obtained by varying piece-wise polynomial fitting. Experimental results performed on standard GRID database show that the scheme performs well even under the influence of illumination and clothing effects. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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