Traffic-Sign-Classification

These are MATLAB codes for traffic sign classification. Database used is German Traffic Sign Database, available for download here: http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset

Some Sample Images:

Images from this database are very life-like and are challenging to classify. They are of different sizes and differently illuminated etc.

We used:

1. Linear Discriminant Analysis

2. Fisher's Linear Discriminant/Fisherfaces

3. Random Forests (in python)

algorithms to classify:

Raw intensity values from Images

Histogram of Oriented Gradients descriptors

To get these codes working, point to the correct directory containing dataset in readHOG.m, readTestHOG.m, readImages.m, readTestImages.m files

A detailed report containing results is availabe in report folder. References are also available in it.

#Note on Random Forests Implementation: We tried to implement our own randomforests class in python. As of the moment, it's not working and has to be debugged. Instead use RF_builtin.py to classify using scikit-learn's randomforest classifier class. As before, edit the file to point to the folder containing dataset.