Object-Aware Image Thumbnailing Using Image Classification and Enhanced Detection of ROI

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 310
  • Download : 0
Thumbnail images are used to display a large collection of photos in various digital devices. It aims for people to browse and search the image collection effectively. The provided thumbnail images are expressed in a much lower resolution compared to the resolution of the original image. Thus, it faces a significant problem of how to represent the content of a given image effectively in a tiny thumbnail image. Many image thumbnailing methods have been presented in literature for this purpose. However, the existing thumbnailing methods are designed to use a single method to all kinds of images, regardless of image contents. On the other hand, the proposed method employs two different thumbnail generation methods either of which is applied according to corresponding image context. To achieve this, we first classify images into two groups by detecting the object existence. Then, an ROI cropping method using a saliency map is presented for images with objects, in order to represent the important region of images in the thumbnail. Images without any interesting objects, such as landscape images, are considered to be resized by using a simple scaling method to maintain the whole image context. Experimental results show that the proposed method yields comparable performance on a variety of datasets.
Publisher
SPRINGER
Issue Date
2016-12
Language
English
Article Type
Article
Keywords

VIDEO; SALIENCY

Citation

MULTIMEDIA TOOLS AND APPLICATIONS, v.75, no.23, pp.16191 - 16207

ISSN
1380-7501
DOI
10.1007/s11042-015-2926-5
URI
http://hdl.handle.net/10203/214216
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0