Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6958409 | Signal Processing | 2016 | 11 Pages |
Abstract
To localize objects in Web images using an invariant descriptor is crucial. The HOG (histogram of oriented gradients) descriptor is used to increase the accuracy of localization. It is a shape descriptor that considers frequencies of gradient orientation in localized portions of an image. This well known descriptor does not cover rotation variations of an object in images. This paper introduces a rotation invariant feature descriptor based on HOG. The proposed descriptor is used in a top-down searching technique that covers the scale variation of the objects in images. The efficiency of this method is validated by comparing the performance with existing research in a similar domain on the Caltech-256 Web dataset. The proposed method not only provides robustness against geometrical transformations of objects but also is computationally more efficient.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Ali Vashaee, Reza Jafari, Djemel Ziou, Mohammad Mehdi Rashidi,