Extraction of Mosaic Regions through Projection and Filtering of Features from Image Big Data

Seok-Woo Jang1

  1. Department of Software, Anyang University
    22, 37-Beongil, Samdeok-Ro, Manan-Gu, Anyang 14028, Korea
    swjang7285@gmail.com

Abstract

When uploading multimedia data such as photos or videos on social network services, websites, and so on, certain parts of the human body or personal information are often exposed. Therefore, it is frequent that the face of a person is blurred out to protect the portrait right of a particular person, and that repulsive objects are covered with mosaic blocks to prevent others from feeling disgusted. In this paper, an algorithm that detects mosaic regions blurring out certain blocks based on the edge projection is proposed. The proposed algorithm initially detects the edge and uses the horizontal and vertical line edge projections to detect the mosaic candidate blocks. Subsequently, geometrical features such as size, aspect ratio and compactness are used to filter the candidate mosaic blocks, and the actual mosaic blocks are finally detected. The experiment results showed that the proposed algorithm detected mosaic blocks more accurately than other methods.

Key words

Video Analysis, Edge Extraction, Geometrical Feature, Filtering, Candidate Verification

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS200227010J

Publication information

Volume 18, Issue 2 (April 2021)
Special Issue on Emerging Services in the Next-Generation Web: Human Meets Artificial Intelligence
Year of Publication: 2021
ISSN: 1820-0214 (Print) 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Jang, S.: Extraction of Mosaic Regions through Projection and Filtering of Features from Image Big Data. Computer Science and Information Systems, Vol. 18, No. 2, 553–574. (2021), https://doi.org/10.2298/CSIS200227010J