Distance transformation algorithms approximations use distance transformation with small neighborhood pixels, defined by masks. There are many different DT approximations applied, and some of them are proposed to be implemented in custom hardware, exploiting the possibilities offered for accelerating the actions required in the proposed algorithm. In this paper, a custom hardware architecture is proposed in order to implement fast 2D distance transformations that are independent of the distance function used. The current implementation concerns the Euclidean distance transform and Kintex7 evaluation board is used for this purpose. Area and synthesis results are presented for various image sizes, while it is observed a speed increase of 98% against the X86 architecture.
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.