Forensic analysis of copy-move forgery in digital images using the stationary wavelets

Three elliptical skin color models are presented for skin color detection. The first one is to model the skin color cluster using a single ellipse ignoring the lightness dependency. It is simple and efficient, and the skin color detection accuracy may be adequate for many applications. In the second model, the skin color ellipse is adapted to different lightness levels to better fit the shape of the skin color cluster. The model is more complex to train, and the computation efficiency is lower, but the skin color detection accuracy is considerably higher. In the third method, an ellipsoid is trained to fit the skin color cluster. It is almost as simple to train as the first model, but the skin color detection accuracy is higher. Having skin color detection accuracy almost as high as the second model, this model is easier to train and may be more efficient in computation.

Lightness

Ellipse

Ellipsoid

Skin Color

Color balance

ICC profile

Color histogram

RGB color model

10.2352/j.imagingsci.technol.2011.55.3.030201

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Visualization of contents archive by contour map representation

Hideyuki Kubota Toshirou Nishida Y. Sumi

Representation

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A Study on Three-dimensional Reconstruction from Old Video Archive

ITE Technical Report; ITE Tech. Rep. (2019)

Takahashi Naoki Makoto Hasegawa

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Recovering scheme for Electronic Documents by Watermark to Signature Seal

The Journal of The Institute of Image Information and Television Engineers (2000)

Munetoshi Iwakiri Kineo Matsui

Signature (topology)

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Textual Ontology and Visual Features Based Search for a Paleontology Digital Library

IEEE Conference Proceedings (2016)

Yang Tian Sompalli Ranjith Guanghui Wang Bo Luo

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Exploration of text collections with hierarchical feature maps

Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '02 (1997)

Dieter Merkl

article Free Access Share on Exploration of text collections with hierarchical feature maps Author: Dieter Merkl Department of Computer Science, Royal Melbourne Institute of Technology, 723 Swanston St., Carlton, VIC 3053, Australia and Institut für Softwaretechnik, Technische Universität Wien, Resselgasse 3/188, A-1040 Vienna, Austria Department of Computer Science, Royal Melbourne Institute of Technology, 723 Swanston St., Carlton, VIC 3053, Australia and Institut für Softwaretechnik, Technische Universität Wien, Resselgasse 3/188, A-1040 Vienna, AustriaView Profile Authors Info & Claims ACM SIGIR ForumVolume 31Issue SIDecember 1997pp 186–195https://doi.org/10.1145/278459.258564Published:01 July 1997Publication History 39citation1,023DownloadsMetricsTotal Citations39Total Downloads1,023Last 12 Months39Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Feature (linguistics)

10.1145/258525.258564

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Text Area Detection in Digital Documents Images Using Textural Features

Lecture notes in computer science (2007)

Ilktan Ar Karsligil M.Elif

Digital Imaging

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