Road Sign Detection and Recognition using Colour Segmentation, Shape Analysis and Template Matching

The paper presents a system for detection and recognition of road signs with red boundaries and black symbols inside. The detection is invariant to varying lighting conditions and shadows. The algorithm is tested on RGB images taken from camera. These images are converted to HSV colour space. Colour...

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Bibliographic Details
Main Authors: Malik, R., Khurshid, J., Ahmad, S.N.
Format: Conference Proceeding
Language:English
Subjects:
Color
Color segmentation
Cybernetics
Detectors
Fuzzy shape detector
Image databases
Image segmentation
Java
Machine learning
Roads
Rotation Invariant
Shadow Invariant
Shape
Template matching
Testing
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Summary:The paper presents a system for detection and recognition of road signs with red boundaries and black symbols inside. The detection is invariant to varying lighting conditions and shadows. The algorithm is tested on RGB images taken from camera. These images are converted to HSV colour space. Colour segmentation for red regions is applied on the whole image. All red regions are labeled forming objects. Each of the red objects is tested for its shape. Final image contains only those red objects which are triangular or circular in shape. Finding the black regions within the accepted red objects area, results in extraction of pictogram. This pictogram is then matched with templates in database, hence recognizing the meaning of road sign. The paper presents a revised edition of fuzzy shape detector and a recognition module that uses template matching to recognize rotated and affine transformed road signs.
ISSN:2160-133X
DOI:10.1109/ICMLC.2007.4370763