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Traffic Sign Recognition

Traffic Sign Recognition. Jacob Carlson Sean St. Onge Advisor: Dr. Thomas L. Stewart. Traffic Sign Recognition. Project Overview System Description Current Functionality Future Work. Traffic Sign Recognition. Project Overview System Description Current Functionality Future Work.

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Traffic Sign Recognition

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  1. Traffic Sign Recognition Jacob Carlson Sean St. Onge Advisor: Dr. Thomas L. Stewart

  2. Traffic Sign Recognition • Project Overview • System Description • Current Functionality • Future Work

  3. Traffic Sign Recognition • Project Overview • System Description • Current Functionality • Future Work

  4. Project Overview Object identification has many applications in various fields. This project aims to identify a traffic sign from a digital image. This would be useful in an autonomous vehicle application. These ideas and methods could also be used in other areas.

  5. Project Overview • The overall objective of this project is to write a program what will identify a traffic sign from a digital photograph. • Traffic signs appear in diverse background situations and, at times, may be partially obscured.

  6. Traffic Sign Recognition • Project Overview • System Description • Current Functionality • Future Work

  7. System Description

  8. System Description • When the program is initialized, an image, previously saved on the system’s hard drive, is loaded for analysis. • At this point, some preliminary analysis will be performed, and preprocessing will be performed manually.

  9. System Description • This portion of the program will gather and analyze color data, and will also perform edge detection. Red Green Blue

  10. System Description • Additional methods (dilation, opening, closing, erosion) may also be applied at this time. • The sign will be classified based on color.

  11. System Description • After classification, the software will highlight the image or “area of interest”. • The software will then write pertinent data to either the screen or an output file.

  12. Traffic Sign Recognition • Project Overview • System Description • Current Functionality • Future Work

  13. Current Functionality • Currently our program divides the color image into the three color planes. • We first look for red signs (stop sign, do not enter, wrong way). Our algorithm currently isolates most red signs effectively. • It can also isolate yellow signs, but this still requires some optimization.

  14. Current Functionality • Initial Image

  15. Current Functionality • Red Plane

  16. Current Functionality • Red Plane, after Thresholding

  17. Current Functionality • Green Plane

  18. Current Functionality • Blue Plane

  19. Current Functionality • Threshold red plane after median filter.

  20. Current Functionality • Sobel Masks – Used for edge detection (differentiation).

  21. Current Functionality • Horizontal Edge Detection using Sobel masks.

  22. Current Functionality • Vertical Edge Detection using Sobel masks.

  23. Current Functionality • Sum of horizontal and vertical edge detection.

  24. Current Functionality • Image after erosion by a line structuring element.

  25. Current Functionality • Image after closing with octagon structuring element.

  26. Current Functionality • Stop sign identified using ‘blob’ recognition techniques.

  27. Current Functionality • Final image with stop sign highlighted.

  28. Traffic Sign Recognition • Project Overview • System Description • Current Functionality • Future Work

  29. Traffic Sign Recognition • Current problem is having the computer recognize that the shape is a stop sign. *

  30. Traffic Sign Recognition • Identifying a region of interest and cropping out the background prior to performing main processing would streamline calculations. • Speed could also be increased by using C or C++ to implement the processing algorithms.

  31. Questions?

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