KEYWORDS: Edge detection, Image processing, Detection and tracking algorithms, Image quality, System identification, Image filtering, Signal to noise ratio, Databases, Warning signs, Intelligence systems
Intelligent transportation system is one of the hot topics of current research, including a very critical technology is automatic identification system of traffic signs. In identification system, since image acquisition is affected by the environment, the resulting image quality is uneven, which requires an algorithm suitable for a variety of quality digital images to identify the type of traffic signs. This paper makes some improvement of the originally perfect Canny edge detection operator, to make it suitable for different images, so we can quickly and accurately detect the image edge, further facilitate matching work, automatically identify traffic signs. Experimental results show that the improved Canny edge detection algorithm is fast, and the detected edge is clear and accurate.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.