NDLI: Fully automatic figure-ground segmentation algorithm based on deep convolutional neural network and GrabCut

Content Provider	IET Digital Library
Author	Fu, Ruigang Li, Biao Gao, Yinghui Wang, Ping
Abstract	Figure-ground segmentation is used to extract the foreground from the background, where the foreground is usually defined as the region containing the most meaningful object of the image. In fact, the algorithms that take advantage of human–computer interaction often attain better performance and they are based on the ‘one-to-one’ model. In this study, the authors present a novel algorithm for figure-ground segmentation based on the GrabCut algorithm, which is a common segmentation algorithm that is user interactive. However, instead of a real user, they attempt to use a pre-trained deep convolutional neural network to interact with GrabCut for completing its job successfully. Weizmann's segmentation evaluation database is used as the test dataset and the results show that their algorithm works well for figure-ground segmentation. While the previous automatic segmentation algorithms are required to rank their segments empirically in order to find the position of the foreground after the segmentation, their algorithm is fully automatic.
Starting Page	937
Ending Page	942
Page Count	6
ISSN	17519659
Volume Number	10
e-ISSN	17519667
Issue Number	Issue 12, Dec (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/10/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0009
Journal	IET Image Processing
Publisher Date	2016-07-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Convolution Deep Convolutional Neural Network Feature Extraction Fully Automatic Figure-ground Segmentation Algorithm GrabCut Algorithm Human Computer Interaction Human-computer Interaction Image Object Image Segmentation Knowledge Engineering Technique Neural Nets Optical, Image And Video Signal Processing Weizmann Segmentation Evaluation Database
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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