Screen content image segmentation using sparse decomposition and total variation minimization

Shervin Minaee, Yao Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sparse decomposition has been widely used for different applications, such as source separation, image classification, image denoising and more. This paper presents a new algorithm for segmentation of an image into background and foreground text and graphics using sparse decomposition and total variation minimization. The proposed method is designed based on the assumption that the background part of the image is smoothly varying and can be represented by a linear combination of a few smoothly varying basis functions, while the foreground text and graphics can be modeled with a sparse component overlaid on the smooth background. The background and foreground are separated using a sparse decomposition framework regularized with a few suitable regularization terms which promotes the sparsity and connectivity of foreground pixels. This algorithm has been tested on a dataset of images extracted from HEVC standard test sequences for screen content coding, and is shown to have superior performance over some prior methods, including least absolute deviation fitting, k-means clustering based segmentation in DjVu and shape primitive extraction and coding (SPEC) algorithm.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages3882-3886
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - Aug 3 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: Sep 25 2016Sep 28 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period9/25/169/28/16

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Fingerprint Dive into the research topics of 'Screen content image segmentation using sparse decomposition and total variation minimization'. Together they form a unique fingerprint.

Cite this