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Intelligent innovations in multimedi...
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Bhattacharyya, Siddhartha, (1975-)
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Intelligent innovations in multimedia data engineering and management
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Intelligent innovations in multimedia data engineering and management/ Siddhartha Bhattacharyya, editor.
其他作者:
Bhattacharyya, Siddhartha,
出版者:
Hershey, Pennsylvania :IGI Global, : [2019],
面頁冊數:
1 online resource (xvi, 316 p.)
內容註:
Chapter 1. Implementation of a reversible watermarking technique for medical images -- Chapter 2. Multimedia data security with recent trends and technologies: a Survey -- Chapter 3. On the implementation of a fragile medical image watermarking technique using saliency and phase congruency -- Chapter 4. Exploring recent advances in digital video steganography and future scope -- Chapter 5. Reversible data hiding: an active forensic framework for digital images -- Chapter 6. Commutative watermarking-encryption of multimedia data based on histograms -- Chapter 7. De-noising of binary image using accelerated local median-filtering approach -- Chapter 8. Analysis of human gait for designing a recognition and classification system -- Chapter 9. Implementation of a hybrid classification method for diabetes -- Chapter 10. Melanoma identification using MLP with parameter selected by metaheuristic algorithms.
標題:
Image processing - Digital techniques. -
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-5225-7107-0
ISBN:
9781522571087 (e-book)
Intelligent innovations in multimedia data engineering and management
Intelligent innovations in multimedia data engineering and management
[electronic resource] /Siddhartha Bhattacharyya, editor. - Hershey, Pennsylvania :IGI Global,[2019] - 1 online resource (xvi, 316 p.)
Includes bibliographical references and index.
Chapter 1. Implementation of a reversible watermarking technique for medical images -- Chapter 2. Multimedia data security with recent trends and technologies: a Survey -- Chapter 3. On the implementation of a fragile medical image watermarking technique using saliency and phase congruency -- Chapter 4. Exploring recent advances in digital video steganography and future scope -- Chapter 5. Reversible data hiding: an active forensic framework for digital images -- Chapter 6. Commutative watermarking-encryption of multimedia data based on histograms -- Chapter 7. De-noising of binary image using accelerated local median-filtering approach -- Chapter 8. Analysis of human gait for designing a recognition and classification system -- Chapter 9. Implementation of a hybrid classification method for diabetes -- Chapter 10. Melanoma identification using MLP with parameter selected by metaheuristic algorithms.
Restricted to subscribers or individual electronic text purchasers.
"This book addresses the challenges encountered in multimedia data management by devising both classical and intelligent techniques. It highlights the essence of multimedia data management and engineering involved"--Provided by publisher.
ISBN: 9781522571087 (e-book)Subjects--Topical Terms:
532550
Image processing
--Digital techniques.
LC Class. No.: TA1637 / .I494 2019e
Dewey Class. No.: 006.6
Intelligent innovations in multimedia data engineering and management
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Chapter 1. Implementation of a reversible watermarking technique for medical images -- Chapter 2. Multimedia data security with recent trends and technologies: a Survey -- Chapter 3. On the implementation of a fragile medical image watermarking technique using saliency and phase congruency -- Chapter 4. Exploring recent advances in digital video steganography and future scope -- Chapter 5. Reversible data hiding: an active forensic framework for digital images -- Chapter 6. Commutative watermarking-encryption of multimedia data based on histograms -- Chapter 7. De-noising of binary image using accelerated local median-filtering approach -- Chapter 8. Analysis of human gait for designing a recognition and classification system -- Chapter 9. Implementation of a hybrid classification method for diabetes -- Chapter 10. Melanoma identification using MLP with parameter selected by metaheuristic algorithms.
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