Shape Teacher
Kathryn Chong Quigley
EPS 209 Matlab
Final Project Presentation
Shape Teacher
Kathryn Chong Quigley
EPS 209 Matlab
Final Project Presentation
Shape Teacher
Kathryn Chong Quigley
EPS 209 Matlab
Final Project Presentation
Shape Teacher
Kathryn Chong Quigley
EPS 209 Matlab
Final Project Presentation
Shape Teacher?
• Smart Phone App
• Teaches Basic Shapes
• Users Identify Shapes Around Them
• Context Increases Learning
Phone App Flowchart
Photos of
objects
Matlab code
Matlab Code
•Looped to process multiple images
•Filter image and make high contrast B&W
•Convert to label matrix and find largest grain
•Using region props for largest grain
•Use parameters to differentiate between shapes
•Print shape name on to the original image.
Shape of
object
identified
Images Used in Prototype
Images Used in Prototype
Regionprops  BoundingBox
Regionprops  BoundingBox
Ecc > 0.8
Regionprops  BoundingBox
Ecc > 0.8
 Nonsymmetrical
Regionprops  BoundingBox
Ecc > 0.8
 Nonsymmetrical  Area / bbox(3) * bbox(4)
> 7.9
Regionprops  BoundingBox
Ecc > 0.8
 Nonsymmetrical  Area / bbox(3) * bbox(4)
> 7.9 
Rectangle!
Decision Tree
Eccentricity differentiates between
symmetric and nonsymmetrical
Ecc > 0.8
Divide Area of largest grain by:
1) Area of the bbox (non sym)
(False / Symmetrical)
(True / Nonsymmetrical)
(pi*(bbox(3)/2)2
Area / (bbox(3) * bbox(4)) > 7.9
Area /
> 1.05
2) Circle using ½ the width of the
bbox (sym)
The final shapes are identified!
(True)Square
(False)Circle
(True)Rectangle
(False)Ellipse
Circle in the Watch
Circle in the Watch
Circle in the Watch
Circle in the Watch
Circle in the Watch
Circle in the Watch
The Shapes Identified