Traffic Sign Detection and Recognition using Random Forest Classifier

Detect and recognize traffic signs using image processing algorithms and machine learning(Random Forest algorithm) --- Accuracy 94%
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
3. Usage
4. Contact

About The Project

Detect and recognize traffic signs using Image Processing algorithms and Machine Learning(Random Forest) with an accuracy of 94%.

Datasets used:

• GTSDB
• GTSRB

Due to time constraint and computational limitations, the dataset has been intentionally reduced to 16000 files. To use entire dataset, try adding more masks!

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Built With

• MATLAB
• Image Processing
• Machine Learning

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Getting Started

This entire project can be fragmented in to two parts:

• Detection
• Recognition

Prerequisites

Things required to make the project a success:

• Knowledge of Image Processing
• Getting around Matlab
• Machine Learning
• Never give up attitude!

Usage

After Image detection has been done!

• Open Hog Feature Extraction file and make the required changes upon your requirement and run it.
• HOG Features will be saved to avoid extraction for every execution.
• Open Training and Model Accuracy file to train the model with extracted features.

  Change the number of decision trees for your desired accuracy! Also check the ROC-AUC and Precision-Recall curves.

• The model will be saved locally.

  Saving time varies from computer to computer

• Move all masks to the current directory so that, Main Funtion file will be in the same level as masks.
• Run the Main Funtion file and you are good to go!!....

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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Contact

Your Name - Praveenterax - [email protected]

Project Link: https://github.com/Praveenterax/Traffic-sign-Detection-Recognition-Matlab-RandomForest

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