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rdf:type
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Description
| - The conventional digital watermarking schemes uses a digital pattern like pseudorandom number sequence, a logo image or a digital signature as the watermark which has limitations in proving ownership of the watermark. This paper proposes a proficient digital watermark generation technique from biometric data which will be unique and can be logically owned to prove ownership. The issue of ownership of digital watermark is addressed in this paper. The biometric pattern of fingerprint is used to generate the digital watermark that has a stamp of ownership. The generated watermark has been studied for uniqueness and identification and has been used to watermark audio signals. Discrete cosine transformation is used for embedding the watermark in the image. Experimental results indicate that the watermark can survive the signal processing and maintain the perceptual properties of the host signal and hence satisfies the design requirements of digital watermarking. The extracte
- The conventional digital watermarking schemes uses a digital pattern like pseudorandom number sequence, a logo image or a digital signature as the watermark which has limitations in proving ownership of the watermark. This paper proposes a proficient digital watermark generation technique from biometric data which will be unique and can be logically owned to prove ownership. The issue of ownership of digital watermark is addressed in this paper. The biometric pattern of fingerprint is used to generate the digital watermark that has a stamp of ownership. The generated watermark has been studied for uniqueness and identification and has been used to watermark audio signals. Discrete cosine transformation is used for embedding the watermark in the image. Experimental results indicate that the watermark can survive the signal processing and maintain the perceptual properties of the host signal and hence satisfies the design requirements of digital watermarking. The extracte (en)
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Title
| - AUTOMATED BRAIN TUMOR SEGMENTATION USING NOVEL FEATURE POINT DETECTOR AND SEEDED REGION GROWING
- AUTOMATED BRAIN TUMOR SEGMENTATION USING NOVEL FEATURE POINT DETECTOR AND SEEDED REGION GROWING (en)
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skos:prefLabel
| - AUTOMATED BRAIN TUMOR SEGMENTATION USING NOVEL FEATURE POINT DETECTOR AND SEEDED REGION GROWING
- AUTOMATED BRAIN TUMOR SEGMENTATION USING NOVEL FEATURE POINT DETECTOR AND SEEDED REGION GROWING (en)
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skos:notation
| - RIV/00216305:26220/13:PU104504!RIV14-MPO-26220___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216305:26220/13:PU104504
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - Brain tumor, feature points, wavelets, canny edge, morphological operations (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - 36th International Conference on Telecommunications and Signal processing
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Burget, Radim
- Říha, Kamil
- Dutta, Malay Kishore
- Singh, Anushikha
- Soni, K. M.
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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number of pages
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http://purl.org/ne...btex#hasPublisher
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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