real time traffic sign analysis
DESCRIPTION
Real Time Traffic Sign Analysis- This subject deals with Recognition and Detection of Traffic sign by Image Processing Techniques...TRANSCRIPT
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REAL TIME TRAFFIC SIGN ANALYSIS
Presented By-Rakesh Ravaso PatilT CO ‘B’ 12276
Guided By-Ms. P. P. Lokhande
R²P
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Overview
Introduction Traffic sign analysis
Color segmentation Edge detection Shape based detection
Recognition Binary Thresholding Recognition and Matching using IPP
Recognition of traffic signs using FPGA hardware How TSR is works? Conclusion
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INTRODUCTION
Advanced Driver Assistance Systems (ADAS) Lane Departure Warning Night Vision Automatic Parking Blind Spot Detection Traffic Sign Recognition
First used In BMW 7 Series Volkswagen Phaeton
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WHY WE REQUIRE THIS?
Sleepy driver crashes SUV on Mumbai-Pune Expressway, 7 passengers killed. (TOI, March 5)
Human error behind most Expressway mishaps. (TOI, March 5)
In 2012, the expressway, witnessed 475 accidents in which 105 people died.
MSRDC plan: Trauma Care & Copter Service CCTV Cameras Truck Terminals Reducing U-Turns
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TRAFFIC SIGN
Sign TypePossible
(Border) ColorsSign Shape
Restricting &
WarningRed, Blue, Black
Triangle,
Rectangle,
Octagon, Circle
Information Blue, Red Rectangle
Highway
InformationGreen Rectangle
Table: Standard Traffic Sign
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REAL TIME TRAFFIC SIGN ANALYSIS
Detection Recognition Problem facing
Illumination affects the color analysis. Occlusion affects the shape analysis. Weather conditions such as rain, snow or fog
affect the shape extraction. Physically damaged or changed surface metal of
traffic signs affects the recognition.
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TRAFFIC SIGN ANALYSIS
Fig: Steps of TSR System
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COLOR SEGMENTATION
Fig: Traffic sign and Red/Blue segmented image
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COLOR SEGMENTATION-ADVANTAGES
Eliminates undesired colors, thus the number of edge pixels in the edge detection process decreases.
The complexity decreases since only edge pixels are processed.
Fault detections decrease in the detection process. Color segmentation gives information about the
border color and the inner color of the sign.
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EDGE DETECTION
Identifying points in a digital image at which the image brightness changes sharply
Fig: Edge image with color segmentation
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SHAPE BASED DETECTION
Types: Triangle, Circle and Rectangle
TRIANGULAR SIGN DETECTION Hough Transform using Slope-Intercept Line equ.
y=a.x + bwhere: x,y are coordinates
a is the slope of the lineb is the constant parameter…
Use of Polar Coordinates instead of Cartesian Coordinates.
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TRIANGULAR SIGN DETECTION
x.cosΘ + y.sinΘ=rWhere: r is distance between line & Origin
Θ is angle from origin to the closest point to line
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TRIANGULAR SIGN DETECTION
Fig: Edge Image of a Triangular Traffic sign
Fig: Detected Lines after applying Hough Transform
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CIRCULAR SIGN DETECTION
Circular Hough Transform using parametric equation of Circle:
(x-xc)² + (y-yc)² = r² Because of Perspective distortion Circular traffic
sign may appear as elliptical. (x-xc)² + k.(y-yc)² = r²
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CIRCULAR SIGN DETECTION
Fig: Detected Circle after applying CHT Fig: Detected Ellipse after applying Ellipse Detection
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RECTANGULAR SIGN DETECTION
Fig: Detected Lines of Rectangular Traffic Sign
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RECOGNITION
A binary image is generated using ROI of the image. Morphological operations are applied to the binary
image in order to remove the unwanted pixels. Informative Pixel Percentage (IPP).
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BINARY THRESHOLDING
ROI is the informative part of the image. Traffic sign consists of only two different colors. One
is the informative color of ROI and the other is the background color.
Fig: Output of Binarization Process
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RECOGNITION AND MATCHING USING IPP
TRIANGULAR SIGN RECOGNITION
Fig: Divided Regions of Triangular Sign
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CIRCULAR, RECTANGULAR SIGN RECOGNITION
Fig: Divided Regions of Circular and Rectangular Sign
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RECOGNITION OF TRAFFIC SIGNS USING FPGA HARDWARE
VIRTEX5-FX70T FPGA XILINX Platform flash PROM DDR2 SDRAM LCD Display
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HOW TSR IS WORKS?
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CONCLUSION
Automatic traffic sign detection and recognition is an important part of an ADAS.
Traffic symbols have several distinguishing features that may be used for their recognition and detection.
There are several factors that can hinder effective detection and recognition of traffic signs.
The performance of the TSR system can be improved with increasing the number of divided regions.
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