Back to articles
Volume: 31 | Article ID: art00009
Frame Detection for Photos of Online Fashion Items
  DOI :  10.2352/ISSN.2470-1173.2019.8.IMAWM-412  Published OnlineJanuary 2019

In the competitive online fashion market place, it is common for sellers to add artificial elements to their product images, with the hope to improve the aesthetic quality of their products. Among the numerous types of artificial elements, we focus on detecting artificial frames in fashion images in this paper and we propose a novel algorithm based on traditional image processing techniques for this purpose. On the other hand, even though deep learning methods have been very powerful and effective in many image processing tasks in recent years, they do have their drawbacks in some cases, rendering them ineffective compared to our method for this particular task. Experimental results on 1000 testing images show that our algorithm has comparable performance with some of the state-of-the-art deep learning models that have been used for classification.

Subject Areas :
Views 26
Downloads 3
 articleview.views 26
 articleview.downloads 3
  Cite this article 

Litao Hu, Jan Allebach, Gautam Glowala, Sathya Sundaram, Perry Lee, "Frame Detection for Photos of Online Fashion Itemsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World,  2019,  pp 412-1 - 412-5,

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2019
Electronic Imaging
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA