Detector of image orientation based on Borda Count

Citations of this article
Mendeley users who have this article in their library.


Accurately and automatically detecting image orientation is a task of great importance in intelligent image processing. In this paper, we present an automatic image orientation detection algorithm based on low-level features: color moments; Harris corner; phase symmetry; edge direction histogram. Support vector machines, statistical classifiers, parzen window classifiers are used in our approach: we use Borda Count as combination rule for these classifiers. Large amounts of experiments have been conducted, on a database of more than 6000 images of real photos, to validate our approach. Discussions and future directions for this work are also addressed at the end of the paper. © 2005 Elsevier B.V. All rights reserved.




Lumini, A., & Nanni, L. (2006). Detector of image orientation based on Borda Count. Pattern Recognition Letters, 27(3), 180–186.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free