Lane Line Detection
Project Objectives (less than 2500 characters)
Project Title
Lane Line Detection
Project Area of Specialization
Project Summary
Summary:
This is an intermediate Python project in machine learning, which is helpful for the data science aspirants to master machine learning and gain expertise using Technology (Artificial Intellegence) to make innovation in 4th industrial revoulution.
In this lane line detection project, we use OpenCV. Before detecting lane lines, we masked remaining objects and then identified the line with Hough transformation.
Project Objectives
The system has an objective to identify the lane marks. The algorithm followed by a Machine is to detect lane markings on the road
By giving the video of the road as an input to the system by using computer vision technology and primarily designed with the objective of reducing the frequency of accidents.
Project Implementation Method
Road Lane-Line Detection with Python & OpenCV:
Using computer vision techniques in Python, we will identify road lane lines in which autonomous cars must run. This will be a critical part of autonomous cars, as the self-driving cars should not cross it’s lane and should not go in opposite lane to avoid accidents.
Frame Masking and The Hough Line Transformation:
To detect white markings in the lane, first, we need to mask the rest part of the frame. We do this using frame masking. The frame is nothing but a NumPy array of image pixel values. To mask the unnecessary pixel of the frame, we simply update those pixel values to 0 in the NumPy array.
After making we need to detect lane lines. The technique used to detect mathematical shapes like this is called Hough Transform. Hough transformation can detect shapes like rectangles, circles, triangles, and lines.
By such Vision through camera a machine recognized its way and run smoothly on its defined track.
Benefits of the Project
Although alot of Benifits of this project some of Main Highlighted Pros are given below:
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Enabled the Machine vision
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A Machine Based Decision.
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Innovation in field of Artificial Intellegence.
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Development in Transportation Industry.
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Convenient to drive.
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Safe and Sound.
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Reduced the rate of Traffic and road Accidents
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A good way to save precious lives sitting in a Machine.
Technical Details of Final Deliverable
Using computer vision techniques in Python, This will identify road lane lines in which autonomous cars must run.
This will be a critical part of autonomous cars, as the self-driving cars should not cross it’s lane and should not go in opposite lane to avoid accidents.
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Robo Car Kit | Equipment | 1 | 3809 | 3809 |
| Arduino | Equipment | 1 | 2056 | 2056 |
| Raspberry pi 4 Model B | Equipment | 1 | 21050 | 21050 |
| Motor Driver | Equipment | 1 | 2080 | 2080 |
| Power Bank | Equipment | 1 | 2240 | 2240 |
| Camera Respberry pi | Equipment | 1 | 2078 | 2078 |
| Capacitors | Equipment | 5 | 452 | 2260 |
| LED's Bulb | Equipment | 2 | 300 | 600 |
| Bread Board | Equipment | 3 | 150 | 450 |
| 555 Timer | Equipment | 1 | 70 | 70 |
| Digital Multimeter | Equipment | 1 | 748 | 748 |
| soldering iron | Equipment | 1 | 16324 | 16324 |
| Copper Wires | Equipment | 6 | 300 | 1800 |
| 6-Pin Jumper Wires | Equipment | 1 | 4020 | 4020 |
| Double sided Tap | Miscellaneous | 2 | 113 | 226 |
| Paper cardboard | Miscellaneous | 15 | 524 | 7860 |
| Line Marker | Miscellaneous | 1 | 150 | 150 |
| Total in (Rs) | 67821 |
If you need this project, please contact me on contact@adikhanofficial.com
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