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Extraction of Region of Interests from Face Images Using Cellular Analysis

Extraction of Region of Interests from Face Images Using Cellular Analysis. Speaker: Han-ping Cheng. Outline. Introduction Proposed Work Results and Discussions Conclusion Future Works. Introduction. Face recognition system: 1. Face detection

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Extraction of Region of Interests from Face Images Using Cellular Analysis

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  1. Extraction of Region of Interests from Face Images Using Cellular Analysis Speaker: Han-ping Cheng

  2. Outline • Introduction • Proposed Work • Results and Discussions • Conclusion • Future Works

  3. Introduction Face recognition system: 1. Face detection - deals with the problem of face localization 2. Feature extraction - finds the presence of facial features like eyes, nose, nostrils etc. 3. Face recognition - compares an input image against the database and reports a match, if exists

  4. Introduction Face localization approaches Utilizing shape information: Ellipse fitting method, Mosaic images, Color information, Facial geometry and symmetry, etc. Facial feature extraction techniques Eigenface approach, 2D Gabor wavelets, and discrete cosine transform (DCT) based approach

  5. Introduction Cellular analysis of a face image • A novel algorithm for extracting the ROIs from face images Algorithm • Adaptive thresholding • Geometric properties of a face

  6. Proposed Work • Face Localization • Constructing the Cellular Regions • Extraction of Regions of Interest

  7. Proposed Work

  8. Proposed Work

  9. Proposed Work The cell is said to contain a portion of the face. (occupied by the object)

  10. Proposed Work • Let n be the number of cells occupied by the face. • Then the following case are possible: • i) n = 0: • not a vertex of the ROI corresponding to the face • n = 1: • iii) n = 2: • iv) n = 3: • v) n = 4:

  11. Proposed Work The type of the vertex:

  12. Proposed Work • Face Localization • Constructing the Cellular Regions • Extraction of Regions of Interest

  13. Proposed Work

  14. Proposed Work • Face Localization • Constructing the Cellular Regions • Extraction of Regions of Interest

  15. Proposed Work • Region containment tree

  16. Ri vj Rj Proposed Work

  17. Proposed Work 1 Region ‘2’ represents the face region 2 6 3 4 5

  18. Proposed Work • Use priori knowledge about the face geometry to extract the ROI: 1. The center of the regions representing the pair of eyes will approximately lie on the same horizontal line 2. The center of the nostril region and mouth region will lie approximately on the vertical axis that passes through the center of the face region

  19. Proposed Work • Region Merging(special case)

  20. Color Images • RGB format • Three different threshold

  21. Results and Discussions • the precision of the extracted ROIs can be • controlled by varying resolution level *c is the length of the cell

  22. Results and Discussions

  23. Results and Discussions

  24. Results and Discussions

  25. Conclusion • Cellular representation of the ROIs • The complexity is controlled by cell size • Adaptive thresholding mechanism for gray-scale and color image • Region containment tree

  26. Future Works 1. Compare with other ROI extraction techniques 2. Designing a face identification system on the basis of the extracted ROI

  27. Thank you !

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