Traffic Sign Recognition

Jacob Carlson Sean St. OngeAdvisor: 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

Project OverviewObject 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.

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.

Traffic Sign Recognition Project Overview System

Description Current

Functionality Future Work

System Description

PreprocessApply Processing

AlgorithmsClassify Sign (if

present)

Highlight ImageRecommend

Appropriate Action

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.

System Description This portion of the

program will gather and analyze color data, and will also perform edge detection.

Red Green Blue

System Description Additional methods (dilation, opening,

closing, erosion) may also be applied at this time.

The sign will be classified based on color.

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.

Traffic Sign Recognition Project Overview System Description Current

Functionality Future Work

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.

Current Functionality Initial Image

Current Functionality Red Plane

Current Functionality Red Plane, after Thresholding

Current Functionality Green Plane

Current Functionality Blue Plane

Current Functionality Threshold red plane after median filter.

Current Functionality Sobel Masks – Used for edge detection

(differentiation).

Current Functionality Horizontal Edge Detection using Sobel masks.

Current Functionality Vertical Edge Detection using Sobel masks.

Current Functionality Sum of horizontal and vertical edge detection.

Current Functionality Image after erosion by a line structuring element.

Current Functionality Image after closing with octagon structuring element.

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

Current Functionality Final image with stop sign highlighted.

Traffic Sign Recognition Project Overview System Description Current

Functionality Future Work

Traffic Sign Recognition Current problem is having the computer

recognize that the shape is a stop sign.

*

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.

Questions?