학술논문
Logo detection in images using HOG and SIFT
Document Type
Conference
Author
Source
2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE) Advances in Information, Electronic and Electrical Engineering (AIEEE), 2017 5th IEEE Workshop on. :1-5 Nov, 2017
Subject
Language
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.