Automatic Recognition of Speed Limits on Speed-Limit Signs by Using Machine Learning

This study describes a method for using a camera to automatically recognize the speed limits on speed-limit signs. This method consists of the following three processes: first (1) a method of detecting the speed-limit signs with a machine learning method utilizing the local binary pattern (LBP) feat...

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Vydáno v:Journal of Imaging Ročník 3; číslo 3; s. 25
Hlavní autor: Miyata, Shigeharu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.09.2017
Témata:
Algorithms
Artificial intelligence
Aspect ratio
Color
Computer applications to medicine. Medical informatics
computer vision
Electronic computers. Computer science
Fractals
Image coding
Image detection
Image processing
Image retrieval
Local binary pattern
Machine learning
Methods
neural network
Neural networks
pattern recognition
pattern recognition; image processing; computer vision; traffic sign; machine learning; Local binary pattern; neural network
Photography
QA75.5-76.95
R858-859.7
Random access memory
Roads & highways
Robotics
Saturation (color)
Shape recognition
Speed limits
TR1-1050
Traffic control
traffic sign
Traffic signs
Vehicles
Japan
ISSN:2313-433X, 2313-433X
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Shrnutí:This study describes a method for using a camera to automatically recognize the speed limits on speed-limit signs. This method consists of the following three processes: first (1) a method of detecting the speed-limit signs with a machine learning method utilizing the local binary pattern (LBP) feature quantities as information helpful for identification, then (2) an image processing method using Hue, Saturation and Value (HSV) color spaces for extracting the speed limit numbers on the identified speed-limit signs, and finally (3) a method for recognition of the extracted numbers using a neural network. The method of traffic sign recognition previously proposed by the author consisted of extracting geometric shapes from the sign and recognizing them based on their aspect ratios. This method cannot be used for the numbers on speed-limit signs because the numbers all have the same aspect ratios. In a study that proposed recognition of speed limit numbers using an Eigen space method, a method using only color information was used to detect speed-limit signs from images of scenery. Because this method used only color information for detection, precise color information settings and processing to exclude everything other than the signs are necessary in an environment where many colors similar to the speed-limit signs exist, and further study of the method for sign detection is needed. This study focuses on considering the following three points. (1) Make it possible to detect only the speed-limit sign in an image of scenery using a single process focusing on the local patterns of speed limit signs. (2) Make it possible to separate and extract the two-digit numbers on a speed-limit sign in cases when the two-digit numbers are incorrectly extracted as a single area due to the light environment. (3) Make it possible to identify the numbers using a neural network by focusing on three feature quantities. This study also used the proposed method with still images in order to validate it.
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ISSN:2313-433X
2313-433X
DOI:10.3390/jimaging3030025