1. Erin Plasse Advisors: Professor Hanson Professor Rudko

2. Introduction  Experiment done in 1960’s by Kenneth Stevens and Dr. Sven Öhman in Sweden  Used a cineradiograph x-ray to take lateral images of the vocal tract  31 utterances and 2 sentences were made  Analyzed how articulators displace over time  45 frames/second

3. Movie Clip

4. Image Processing  Perkell (1969)- Used manual methods to make tracings of the images

5. Typical Tracing Perkell (1969) used manual

6. Typical Analysis Perkell (1969) used manual measures

7. Goals & Parameters  Design an algorithm in MATLAB to automate the tracings using edge detection methods  Trace certain articulators, such as, lips, velum, epiglottis, hyoid bone, etc.  Results should be similar to the original tracings  Only 13 utterances were analyzed  Obtain tracings for the 20 utterances not analyzed by Perkell (1969)  Manual extraction is time consuming  Smooth and continuous curves

8. Design Alternatives  Snakes: Active Contour Models  Matlab script written by Eric Debreuve  Chan-Vese Region Based Segmentation Algorithm  Matlab script written by Shawn Lankton  EdgeTrak System for Ultrasound images  VIMS Lab, University of Delaware  Customize one of above to create own design for the data

9. Snakes: Active Contour Models Michael Kass  Snake: Energy minimizing spline guided by external forces  Image forces pull it toward lines and edges  MATLAB code written by Eric Debreuve  Only worked with binary images

10. Chan-Vese Algorithm  Region based segmentation  Use homogeneity of intensity in a region as the constraint  Only applicable to closed contours  Uses an initial mask region  MATLAB script written by Shawn Lankton

11. Pharynx using Chan-Vese

12. EdgeTrak System  Li, Kambhamettu, Stone  Uses gradient image forces and intensity information in local regions  Energy definition for snakes:  E Total = α E int + β E ext  Energy band gap  External energy is redefined for EdgeTrak as:  E′ ext (vi) = E band (vi) E ext (vi)  Not effective for closed contours  Good for tracking tongue in noisy images with high- contrast unrelated edges

13. Energy Minimization Band Main contribution of EdgeTrak method, finds the intensity of the regions.  Energy band regions are found around each snake element  Find mean intensity difference between regions  Find new external energy using band energy  Minimize total energy using dynamic programming

14. EdgeTrak Program

15. The Final Design  Used methods from both the EdgeTrak System, Chan-Vese, and snake methods.  Implemented using MATLAB  Used only the image gradient to find edges  Tongue is the articulator that is focused on

16. MATLAB Code  User picks 5 points  33 snake elements found using spline interpolation  Computes internal and external energy of initial snake elements  Computes internal and external energies of points surrounding each initial point  Finds the surrounding point with the lowest energy, this becomes new point  New contour is graphed

17. MATLAB Code Demo %Edge_trak_demo %Coded by Erin Plasse

18. Final Results Results- o Energy of original snake = -96.9553 o Energy of new snake = 1.2244 o Percent change Snake energy = 101.2629 Alpha =.2, Beta =.8, Delta = 5

19. E_snake_orig = -21.8775 E_snake_new = -0.5480 Percent_change_Snake_energy = 97.495

20. Initial Points Final Points

21. Application to other articulators

22. Cont.

23. Future Work  Apply the contour model to a sequence of consecutive frames  Find more articulators  Use the intensity method for external energy as described in the Edge Trak program

24. References  Perkell, Joseph S.. Physiology of Speech Production: Results and Implications of a Quantitative Cineradiographic Study. Cambridge, MA: The MIT Press, 1969.  Stevens, Kenneth and Öhman, Dr. Sven. (1963). “Cineradiographic Studies of speech:procedures and objectives.” J. Acoust. Soc. Am., 35, 1889.  M. Kass, A. Witkin, and D. Terzopoulos, “Snakes: Active Contour Models,” Int. J. Comput. Vis., vol. 1, pp. 321-331, 1988.  T.F. Chan, L.A. Vese. Active Contours Without Edges. IEEE Trans. On Img. Processing., vol. 10, pp.266-277, 2001.  M. Li, C. Kambhametti, M. Stone. Automatic Contour Tracking in Ultrasound Images. 2004.

25. Questions?