Shape Recognition

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Shape Recognition . March Program Review Team Tillamook. The Team. Team Members: Kim Tabac (Spring Team Lead) Bethany Nemeth (Fall Team Lead) Hailee Kenney (Web Master) Ross Hallauer ( VIP ) Advisors: Aziz Inan (Faculty) Walt Harrison (Industry). Inspiration. - PowerPoint PPT Presentation

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Shape Recognition March Program Review

Team Tillamook

The TeamTeam Members:

★ Kim Tabac (Spring Team Lead)★ Bethany Nemeth (Fall Team Lead)★ Hailee Kenney (Web Master)★ Ross Hallauer (VIP)

Advisors: ★ Aziz Inan (Faculty)★ Walt Harrison (Industry)

Inspiration★ Image processing = AWESOME!

○ Analysis and manipulation of digital images■ Digital photography■ Face recognition technology■ Computer graphics (CG)■ Industrial applications

★ Our project:○ Manipulate image to simplify analysis○ Analyze updated image and interpret

Background★ Recognizes and counts the number of shapes

(circle, triangle, or square) that pass under the camera

Vision★Increase efficiency and organization★Automation makes device more

relatable to real-life applications ★User-friendly operation

Parameters★Shapes

○ Triangle, Circle, Square★Color

○ Black and White★Orientation

Approach★Sense-Process-Display★Determined components

○ Arduino MEGA○ EEPROM – MOSIS○ Camera○ ArduCAM/LCD Screen○ Stepper Motor

Architecture★Hardware Components

Architecture

320x240 8x6

★Software Components

Architecture

Architecture

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Architecture★Mechanical Components

Results★ No quantitative

data

★ Data represented by comparing expected shape with shape that was recognized

Expected Shape

Shape Recognized

Expected Shape

Shape Recognized

Square Square ✓ Circle Circle ✓

Circle Circle ✓ Square Square ✓

Triangle Triangle ✓ Triangle Triangle ✓

Square Square ✓ Square Square ✓

Circle Circle ✓ Triangle Triangle ✓

Triangle Triangle ✓

Hardware Challenges★MOSIS

○ Large schematic○ B^2 Logic Limitations

★LCD Display○ ArduCAM shield

★Power supply★Hardware Placement

Software Challenges★Arduino memory limitations

○ Image data○ Large numbers

★Poor Documentation★Coordinating Hardware Components

○ Track, LCD, Camera, On/Off Switch

Demonstration

https://www.dropbox.com/s/uy1qmxnhpcagp3t/00001.MTS

Future Enhancements★Recognize other shapes

○ modify lookup tables

★Incorporate color to identify shapes○ use RGB values rather than converting

averaged RGB pixel values to a black or white value

★Reduce image processing time

Conclusion★Project overview★Architecture (hardware, software,

mechanical components)★Results★Hardware and software challenges★Demonstration