NDLI: Method for recognition of numbers on speed limit signs utilizing an eigen space method based on the KL transform

Content Provider	IEEE Xplore Digital Library
Author	Miyata, S. Takehara, S. Sakai, H. Ishikawa, T.
Copyright Year	2012
Description	Author affiliation: IHI Inspection & InstrumentationCo., Ltd, 1-22-13, Ooi, Shinagawa, Tokyo, Japan (Ishikawa, T.) \|\| School of Engr., Hiroshima, Dept. of Intelligent Mech. Engr., Kink U., Higashi-Hiroshima, Japan (Miyata, S.; Takehara, S.; Sakai, H.)
Abstract	This study explains that a method utilizing the eigen spaces obtained by the KL transform for automatic recognition by camera of the speed on a speed limit sign has the following advantages: it is robust in response to changes in intensity patterns caused by the direction the sign is facing and by the amount of light striking the sign, and it is able to reduce the recognition processing time by reducing the number of feature vector dimensions during analysis. The method for recognition of traffic signs previously proposed by the authors of this study was a method for recognition based on extracting geometric shapes from the sign and recognizing them based on their aspect ratios. As such, this method was not able to identify the numbers on a speed limit sign, all of which have identical aspect ratios. It will be shown that the method in this study is able to recognize nearly all speed limits indicated on traffic signs within several 100s of ms after image acquisition. This method was applied to still images and its effectiveness was verified from the perspective of the following requirements for providing accurate information concerning the vehicle surroundings to the driver: high processing speed, high recognition accuracy, detection of all detectable objects without omission, and robustness in response to changes in the surrounding environment and to geometric changes in the sign image as the vehicle approaches it.
Starting Page	377
Ending Page	382
File Size	261873
Page Count	6
File Format	PDF
ISBN	9781467318716
e-ISBN	9781467318723
e-ISBN	9781467318709
DOI	10.1109/ICARCV.2012.6485188
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vectors Vehicles Feature extraction Image recognition Transforms Pattern recognition Cameras Eigen space method Image processing Computer vision Traffic sign KL transform
Content Type	Text
Resource Type	Article

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