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Use the dental radiograph “teeth_sample.png” in the Files section. The objective
Use the dental radiograph “teeth_sample.png” in the Files section. The objective is to detect the gaps (intensity valleys) between upper and lower teeth (horizontally oriented gap) as well as between teeth (vertically oriented gaps) in the x-ray, as described in (Jain and Chen, 2004), the slides and as was presented in class. As a preprocessing step, you may want to enhance the image (contrast); for example, in Matlab you can see: https://www.mathworks.com/help/images/adaptive-histogram-equalization.html. However, you can use any filter, or cascade of filters, to achieve what you consider as “good” input.
Jain, A.K., and Chen, H. (2004). Matching of dental X-ray images for human identification. Pattern Recognition, 37:1519-1539.
Suggestion: You may want to first detect the gap between upper and lower teeth, and then the gaps between teeth in the upper section and lower section separately. For the gaps between teeth, you can either assume a priori the number of gaps, or calculate them. Remember: there is a single gap between upper and lower teeth as (global) minimum in average intensity profile (you assume this anyway), while there are multiple (local) minima corresponding to the gaps between teeth.
The calculated gaps should be approximated with lines, 2nd degree polynomial for upper-lower, and 1st degree (straight lines) between teeth.
Input: dental radiograph image
Output: original image with calculated lines superimposed on the image
Submit:
Matlab/Python code with any additional external functions you used. [7pts]
A screen recording of your execution. [3pts]
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