TrafficComputerVision

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TrafficComputerVision

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Computer Vision for Driver Assistance Systems with Emgu CV

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# Computer Vision for Driver Assistance Systems
[![Emgu CV](https://avatars1.githubusercontent.com/u/2035816?v=3&s=40)](https://github.com/emgucv/emgucv)
## Overview
This repository contains basic applications for traffic sign recognition and lane detection. The code is written in C# .NET and uses Emgu CV (3.1.0.2504) as wrapper for OpenCV.

## TrafficSignRec
A SURF (Speeded up robust features) based detection and recognition tool. It uses the homography with RANSAC to increase stability. A set of known signs is matched with candidates in the image.

![TrafficSignRec demo](https://github.com/anthony-mestdach/TrafficComputerVision/blob/master/Code/Results/TrafficSignRec/Afbeelding1.png)

## HaarCascadeDetector
A Haar based sign detector. Multiple Haar cascade files are included to detect a 90km/h speed limit sign (Belgian).

![HaarCascadeDetector demo](https://github.com/anthony-mestdach/TrafficComputerVision/blob/master/Code/Results/HaarCascadeDetector/demo.png)

## LaneDetection
A lane detector based on white or yellow road markings. This code is conceptualy based on the Udacity 'Self-Driving Car Engineer Nanodegree' program.

![LaneDetection demo](https://github.com/anthony-mestdach/TrafficComputerVision/blob/master/Code/Results/LaneDetection/LaneDetection.gif)

## Installation
1) Download and install 'emgucv-windesktop_x64-cuda 3.1.0.x' from https://sourceforge.net/projects/emgucv/files/emgucv/3.1.0/
2) Clone or download this repository
3) Open TrafficComputerVision/Code/TrafficComputerVision/TrafficComputerVision.sln
4) Update the references in the projects to your Emgu installation.
5) Build for x64

All necessary test data can be found under TrafficComputerVision/Code/TestData/

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