Lane Line Detection

Project Title

Lane Line Detection

Project Area of Specialization Artificial IntelligenceProject 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:

• Enabled the Machine vision

• A Machine Based Decision.

• Innovation in field of Artificial Intellegence.

• Development in Transportation Industry.

• Convenient to drive.

• Safe and Sound.

• Reduced the rate of Traffic and road Accidents

• 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 HW/SW integrated systemCore Industry TransportationOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	67821
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