This document describes a system comprising a Pedestrian Detection System (PDS) and Lane Detection and Warning System (LDWS) for medium-class cars. It was created by group members Sanket R. Borhade, Manthan N. Shah, and Pravin D. Jadhav. The system uses cameras to detect lanes and pedestrians, with the goal of reducing traffic accidents. It applies techniques like Hough transforms and image segmentation for lane detection and a two-step framework for pedestrian detection. The results are then indicated visually or audibly to the driver.

1. Group Members:Sanket R. Borhade BE-E-16
Manthan N. Shah BE-G-65
Pravin D. Jadhav BE-E-41

2. Need Analysis
• 41% of the total traffic accident casualties are
due to abnormal lane changing.
• More than 535 pedestrians die in road
accidents every year.
• Pune City has the highest rate of accidents
amongst 27 other cities in the India.
• Need for cost effective life saving tool.
• Easy to install in any locomotive.

3. Introduction
• Video-based car navigation systems are
emerging as the next generation technology.
• Object information is gathered via cameras
and then, feature extraction is performed to
obtain edge, colour, object details.
• We are developing a system which comprises
Pedestrian Detection System(PDS) and Lane
Detection and Warning System(LDWS) for
Medium-Class Cars Worldwide.

4. Overview (LDWS)
Input image
Selected lane and position
Indicator on screen
1. A novel technique is used to recognize lane for a various road and
illumination, lane markings conditions such as damaged road surfaces blocked
by a car, shadow, backlights, etc.
2. The basic transform used will be HOUGH transform along with the
segmentation of image concept to detect the lanes without any errors or
flaws.

5. Overview

6. Overview (PDS)
• To achieve high detection speed
with good detection performance,
a Two-step framework method
was proposed.

7. System Block Diagram
Input image
from camera
Detection of
lane or
pedestrian
Indicating the
result by
means of
visuals or
audio

8. Camera
• Color Camera
Detection under normal /Day conditions
• IR Camera
Detection in night/ low light conditions

9. Lane Detection
• Segmentation
Increasing the detection Rate
• Hough Transform
Used for Classification

10. Pedestrian Detection
• 2 Step Method

11. Pedestrian Detection Contd.
• Haar like features
• Triangular Feature Set
• Edgelet
• Shapelet

12. Results

13. Hardware Details
o TMS302C6703
Highest-Performance Floating Point DSP
Advanced Very Long Instruction Word (VLIW)
TMS320c76x DSP Core
32-Bit External Memory Interface
o CMOS Camera
o IR Camera
o Speed Sensor

14. Advantages
•
•
•
•
Combination of both LDW and PD systems
Improved speed and detection rate
Low False Rate
Intended for low cost applications

15. Applications
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•
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Vehicle Driver Assistance Systems
Automated Surveillance
Military Application
Security

16. Thank you