An Effective Watermarking Method Based on Energy Averaging in Audio Signals
Methods based on discrete cosine transform (DCT) have been proposed for digital watermarking of audio signals; however, the watermark is often vulnerable to data compression and signal processing. This paper presents an effective audio watermarking method by energy averaging of DCT coefficients such...
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| Veröffentlicht in: | Mathematical problems in engineering 2018-01, Vol.2018 (2018), p.1-8 |
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| creator | Tsai, S. E. Yang, S. M. |
| description | Methods based on discrete cosine transform (DCT) have been proposed for digital watermarking of audio signals; however, the watermark is often vulnerable to data compression and signal processing. This paper presents an effective audio watermarking method by energy averaging of DCT coefficients such that an audio signal with watermark is robust to data processing. The method is to divide an audio signal into segments by three parameters defining the segment length, the segment sequence of watermark location, and the frequency range of DCT coefficients for watermark location. An error correcting code is also integrated to improve audio signal quality after watermarking. Experimental results show that the method is robust to data compression and many other kinds of signal processing. No original signal is required for decoding the watermark. Comparison of watermarking performance with a recent work validates that the watermarking method has better audio quality and higher robustness. |
| doi_str_mv | 10.1155/2018/6420314 |
| format | Article |
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E. ; Yang, S. M.</creator><contributor>Francomano, Elisa ; Elisa Francomano</contributor><creatorcontrib>Tsai, S. E. ; Yang, S. M. ; Francomano, Elisa ; Elisa Francomano</creatorcontrib><description>Methods based on discrete cosine transform (DCT) have been proposed for digital watermarking of audio signals; however, the watermark is often vulnerable to data compression and signal processing. This paper presents an effective audio watermarking method by energy averaging of DCT coefficients such that an audio signal with watermark is robust to data processing. The method is to divide an audio signal into segments by three parameters defining the segment length, the segment sequence of watermark location, and the frequency range of DCT coefficients for watermark location. An error correcting code is also integrated to improve audio signal quality after watermarking. Experimental results show that the method is robust to data compression and many other kinds of signal processing. No original signal is required for decoding the watermark. Comparison of watermarking performance with a recent work validates that the watermarking method has better audio quality and higher robustness.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2018/6420314</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; Audio data ; Audio signals ; Data compression ; Data processing ; Decoding ; Decomposition ; Digital signal processors ; Digital watermarking ; Discrete cosine transform ; Energy ; Error correcting codes ; Error correction ; Error correction & detection ; Methods ; Multimedia ; Signal processing ; Signal quality ; Speech ; Spread spectrum ; Wavelet transforms</subject><ispartof>Mathematical problems in engineering, 2018-01, Vol.2018 (2018), p.1-8</ispartof><rights>Copyright © 2018 S. E. Tsai and S. M. Yang.</rights><rights>Copyright © 2018 S. E. Tsai and S. M. Yang. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c360t-a9e31bc4dbc1b917d0f4e543552a25f7ced0e39981bb7b16ce0a3c9b550898ef3</citedby><cites>FETCH-LOGICAL-c360t-a9e31bc4dbc1b917d0f4e543552a25f7ced0e39981bb7b16ce0a3c9b550898ef3</cites><orcidid>0000-0001-5946-6970 ; 0000-0002-7627-0213</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><contributor>Francomano, Elisa</contributor><contributor>Elisa Francomano</contributor><creatorcontrib>Tsai, S. E.</creatorcontrib><creatorcontrib>Yang, S. M.</creatorcontrib><title>An Effective Watermarking Method Based on Energy Averaging in Audio Signals</title><title>Mathematical problems in engineering</title><description>Methods based on discrete cosine transform (DCT) have been proposed for digital watermarking of audio signals; however, the watermark is often vulnerable to data compression and signal processing. This paper presents an effective audio watermarking method by energy averaging of DCT coefficients such that an audio signal with watermark is robust to data processing. The method is to divide an audio signal into segments by three parameters defining the segment length, the segment sequence of watermark location, and the frequency range of DCT coefficients for watermark location. An error correcting code is also integrated to improve audio signal quality after watermarking. Experimental results show that the method is robust to data compression and many other kinds of signal processing. No original signal is required for decoding the watermark. Comparison of watermarking performance with a recent work validates that the watermarking method has better audio quality and higher robustness.</description><subject>Algorithms</subject><subject>Audio data</subject><subject>Audio signals</subject><subject>Data compression</subject><subject>Data processing</subject><subject>Decoding</subject><subject>Decomposition</subject><subject>Digital signal processors</subject><subject>Digital watermarking</subject><subject>Discrete cosine transform</subject><subject>Energy</subject><subject>Error correcting codes</subject><subject>Error correction</subject><subject>Error correction & detection</subject><subject>Methods</subject><subject>Multimedia</subject><subject>Signal processing</subject><subject>Signal quality</subject><subject>Speech</subject><subject>Spread spectrum</subject><subject>Wavelet transforms</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqF0D1PwzAQBmALgUQpbMzIEiOE-uw4ccZQlQ9RxAAItshxzqkLJMVJi_rvSZRKjEzvDY9Ody8hp8CuAKSccAZqEoWcCQj3yAhkJAIJYbzfzYyHAXDxfkiOmmbJGAcJakQe0orOrEXTug3SN92i_9L-w1UlfcR2URf0WjdY0LpjFfpyS9MNel32wFU0XReups-urPRnc0wObBd4sssxeb2ZvUzvgvnT7f00nQdGRKwNdIICchMWuYE8gbhgNkQZCim55tLGBguGIkkU5HmcQ2SQaWGSXEqmEoVWjMn5sHfl6-81Nm22rNe-vyDjLIoEF4IlnboclPF103i02cq77rdtBizr68r6urJdXR2_GPjCVYX-cf_ps0FjZ9DqP82ZEkqJX86Ccpc</recordid><startdate>20180101</startdate><enddate>20180101</enddate><creator>Tsai, S. 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M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c360t-a9e31bc4dbc1b917d0f4e543552a25f7ced0e39981bb7b16ce0a3c9b550898ef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>Audio data</topic><topic>Audio signals</topic><topic>Data compression</topic><topic>Data processing</topic><topic>Decoding</topic><topic>Decomposition</topic><topic>Digital signal processors</topic><topic>Digital watermarking</topic><topic>Discrete cosine transform</topic><topic>Energy</topic><topic>Error correcting codes</topic><topic>Error correction</topic><topic>Error correction & detection</topic><topic>Methods</topic><topic>Multimedia</topic><topic>Signal processing</topic><topic>Signal quality</topic><topic>Speech</topic><topic>Spread spectrum</topic><topic>Wavelet transforms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tsai, S. 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| subjects | Algorithms Audio data Audio signals Data compression Data processing Decoding Decomposition Digital signal processors Digital watermarking Discrete cosine transform Energy Error correcting codes Error correction Error correction & detection Methods Multimedia Signal processing Signal quality Speech Spread spectrum Wavelet transforms |
| title | An Effective Watermarking Method Based on Energy Averaging in Audio Signals |
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