@inproceedings{
 title = {DWT-DCT based blind audio watermarking using Arnold scrambling and Cyclic codes},
 type = {inproceedings},
 year = {2016},
 keywords = {Arnold Transform,Copyright enforcement,Digital Media,Error Correcting Codes,Scrambling},
 id = {ba9e42ac-8549-32f5-9646-0e2e1115fca4},
 created = {2018-09-06T11:22:39.875Z},
 file_attached = {false},
 profile_id = {11ae403c-c558-3358-87f9-dadc957bb57d},
 last_modified = {2018-09-06T11:22:39.875Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {© 2016 IEEE. Currently over the millions of digital audio files such as digital songs are copied illegally during file-sharing over the networks. It has resulted as the loss of revenue for music and broadcasting industries. The traditional protection schemes are no longer useful to protect copyright and ownership of multimedia objects. These challenges have prompted significant research in digital audio watermarking for protection and authentication. It helps to prevent forgery and impersonation of audio signal. In this paper, a novel audio watermarking based algorithm is proposed using Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT). Furthermore, the Arnold transform and error correction technique are utilized to improve the performance of proposed algorithm. The performance is measured using Bit Error Rate (BER), Peak Sound to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the extracted watermark and original watermark. The experimental results show excellent resilience against typical signal processing attacks compared to the previous algorithm. The performance is improved in terms of BER for 0-3.9%, PSNR higher than 62-db and Structural Similarity Index (SSIM) from 0.99 to 1.},
 bibtype = {inproceedings},
 author = {Subir, undefined and Joshi, A.M.},
 doi = {10.1109/SPIN.2016.7566666},
 booktitle = {3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016}
}

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The traditional protection schemes are no longer useful to protect copyright and ownership of multimedia objects. These challenges have prompted significant research in digital audio watermarking for protection and authentication. It helps to prevent forgery and impersonation of audio signal. In this paper, a novel audio watermarking based algorithm is proposed using Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT). Furthermore, the Arnold transform and error correction technique are utilized to improve the performance of proposed algorithm. The performance is measured using Bit Error Rate (BER), Peak Sound to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the extracted watermark and original watermark. The experimental results show excellent resilience against typical signal processing attacks compared to the previous algorithm. The performance is improved in terms of BER for 0-3.9%, PSNR higher than 62-db and Structural Similarity Index (SSIM) from 0.99 to 1.","bibtype":"inproceedings","author":"Subir, undefined and Joshi, A.M.","doi":"10.1109/SPIN.2016.7566666","booktitle":"3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016","bibtex":"@inproceedings{\n title = {DWT-DCT based blind audio watermarking using Arnold scrambling and Cyclic codes},\n type = {inproceedings},\n year = {2016},\n keywords = {Arnold Transform,Copyright enforcement,Digital Media,Error Correcting Codes,Scrambling},\n id = {ba9e42ac-8549-32f5-9646-0e2e1115fca4},\n created = {2018-09-06T11:22:39.875Z},\n file_attached = {false},\n profile_id = {11ae403c-c558-3358-87f9-dadc957bb57d},\n last_modified = {2018-09-06T11:22:39.875Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n private_publication = {false},\n abstract = {© 2016 IEEE. 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The experimental results show excellent resilience against typical signal processing attacks compared to the previous algorithm. The performance is improved in terms of BER for 0-3.9%, PSNR higher than 62-db and Structural Similarity Index (SSIM) from 0.99 to 1.},\n bibtype = {inproceedings},\n author = {Subir, undefined and Joshi, A.M.},\n doi = {10.1109/SPIN.2016.7566666},\n booktitle = {3rd International Conference on Signal Processing and Integrated Networks, SPIN 2016}\n}","author_short":["Subir","Joshi, A."],"biburl":"https://bibbase.org/service/mendeley/11ae403c-c558-3358-87f9-dadc957bb57d","bibbaseid":"subir-joshi-dwtdctbasedblindaudiowatermarkingusingarnoldscramblingandcycliccodes-2016","role":"author","urls":{},"keyword":["Arnold Transform","Copyright enforcement","Digital Media","Error Correcting Codes","Scrambling"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://bibbase.org/service/mendeley/11ae403c-c558-3358-87f9-dadc957bb57d","dataSources":["2252seNhipfTmjEBQ"],"keywords":["arnold transform","copyright enforcement","digital media","error correcting codes","scrambling"],"search_terms":["dwt","dct","based","blind","audio","watermarking","using","arnold","scrambling","cyclic","codes","subir","joshi"],"title":"DWT-DCT based blind audio watermarking using Arnold scrambling and Cyclic codes","year":2016}