Volume 13 Number 12 (Dec. 2018)
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JCP 2018 Vol.13(12): 1395-1402 ISSN: 1796-203X
doi: 10.17706/jcp.13.12.1395-1402

A Survey of Multi-panel Image Segmentation Methods

Farrukh Jabeen, Mushtaq Ali, Amanullah Baloch, Faqir Gul
Department of Information Technology, Hazara University, Mansehra, KP, Pakistan.
Abstract—Multi-panel images play a vital role in describing complicated situations; however, their availability degrades the retrieval accuracy of image retrieval systems. For improving the accuracy of image retrieval systems, the researchers proposed different approaches for the segmentation of multi-panel images into their constituent sub-images. In this paper, five multi-panel image segmentation approaches are reviewed: (1) Manual Segmentation, (2) Inter-panel Boundary Detection, (3) Cluster Based Approach, (4) Sub-panel Label Detection, and (5) Panel Boundary Detection. We discuss the performance metrics used for the evaluation of these proposed approaches. An overview of the datasets used in the literature is also provided. The practical aspects of sub-image separation are finally considered.

Index Terms—Image segmentation, boundary detection, subpanel label detection, OCR.

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Cite: Farrukh Jabeen, Mushtaq Ali, Amanullah Baloch, Faqir Gul, " A Survey of Multi-panel Image Segmentation Methods," Journal of Computers vol. 13, no. 12, pp. 1395-1402, 2018.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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