@inproceedings{364ebdc9d135409aa66f5cb7c00b5808,
title = "Logo detection in images using HOG and SIFT",
abstract = "In this paper we present a study of logo detection in images from a media agency. We compare two most widely used methods-HOG and SIFT on a challenging dataset of images arising from a printed press and news portals. Despite common opinion that SIFT method is superior, our results show that HOG method performs significantly better on our dataset. We augment the HOG method with image resizing and rotation to improve its performance even more. We found out that by using such approach it is possible to obtain good results with increased recall and reasonably decreased precision.",
author = "Jans Glagolevs and Karlis Freivalds",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering, AIEEE 2017 ; Conference date: 24-11-2017 Through 25-11-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/AIEEE.2017.8270535",
language = "English",
isbn = "9781538641385",
series = "Proceedings of the 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering, AIEEE 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--5",
editor = "Andrejs Romanovs and Dalius Navakauskas and Armands Senfelds",
booktitle = "Proceedings of the 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering, AIEEE 2017",
address = "United States",
}