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Image Hiding on Audio Subband Based On Centroid in Frequency Domain BUDIMAN, GELAR; SAFITRI, IRMA; SIREGAR, RIZKY DAMARJATI
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 1 (2019): ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i1.29

Abstract

ABSTRAKAudio watermarking adalah mekanisme penyembunyian data pada audio. Metode penyembunyian data yang digunakan dalam penulisan ini adalah Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), Centroid dan Quantization Index Modulation (QIM). Langkah pertama adalah host audio tersegmentasi menjadi beberapa frame. Kemudian sub-band terpilih diubah oleh FFT dengan mengubah domain sub-band dari waktu ke frekuensi. Proses centroid digunakan untuk menemukan titik pusat frekuensi untuk lokasi penyisipan untuk mendapatkan output yang lebih stabil. Proses penyematan dilakukan dengan QIM. Kinerja watermarking oleh parameter yang disesuaikan memperoleh nilai imperceptibility dengan Signal to Noise Ratio (SNR) > 21 dB, Mean Opinion Score (MOS)> 3.8 dengan kapasitas = 86.13 bps. Selain itu, untuk sebagian besar file audio terwatermark yang diserang, metode ini tahan terhadap beberapa serangan seperti Low Pass Filter (LPF) dengan fco> 6 kHz, Band Pass Filter (BPF) dengan fco 50 Hz - 6 kHz, Linear Speed Change (LSC) dan MP4 Compression dengan Bit Error Rate (BER) kurang dari 20%.Kata kunci: FFT, subband, LWT, Centroid, Audio Watermarking, QIM ABSTRACTAudio watermarking is a mechanism for hiding data on audio. Data hiding methods used in this paper are Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), Centroid and Quantization Index Modulation (QIM). The first step is to segment host audio into several frames, then the selected sub-band is changed by the FFT by changing the sub-band domain from time to frequency. The centroid process is used to find the center of frequency for the insertion location to get a more stable output. The embedding process is done by QIM. The watermarking performance by adjusted parameters obtains the imperceptibility value with Signal to Noise Ratio (SNR)> 21 dB, Mean Opinion Score (MOS)> 3.8 with a capacity = 86.13 bps. In addition, for most of attacked watermarked audio files, this method is resistant to several attacks such as Low Pass Filter (LPF) with fco> 6 kHz, Band Pass Filter (BPF) with fco 50 Hz - 6 kHz, Linear Speed Change (LSC) and MP4 Compression with Bit Error Rate (BER) less than 20%.Keywords: FFT, subband, LWT, Centroid, Audio Watermarking, QIM
QIM - Based Audio Watermarking with Combination Technique of DCT-QR-CPT RENDRAGRAHA, RENDY DWI; BUDIMAN, GELAR; SAFITRI, IRMA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 1 (2019): ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i1.112

Abstract

ABSTRAKAudio watermarking adalah teknik memasukkan informasi ke dalam file audio dan untuk melindungi hak cipta data digital dari distribusi ilegal. Makalah ini memperkenalkan audio stereo watermarking berdasarkan Quantization Index Modulation (QIM) dengan teknik gabungan Discrete Cosine Transform (DCT) - QRCartesian Polar Transform (CPT). Host audio dibagi menjadi beberapa frame, selanjutnya setiap frame ditransformasi oleh DCT, kemudian output DCT diuraikan menjadi matriks orthogonal dan matriks segitiga menggunakan metode QR. Selanjutnya, CPT mengubah dua koefisien kartesian dari matriks segitiga (R) pada posisi (1,1) dan (2,2) menjadi koefisien polar. Setelah itu, penyisipan dilakukan pada koefisien polar oleh QIM. Hasil simulasi menunjukkan bahwa imperseptibilitas audio terwatermark berkualitas baik dengan Signal to Noise Ratio (SNR)> 20, Mean Opinion Score (MOS)> 4 dan tahan terhadap serangan seperti Low Pass Filter (LPF) dan Band Pass Filter (BPF) dengan cut off 25-6k, resampling, Linear Speed Change (LSC) dan MP3 Compression dengan rate diatas 64 kbps.Kata kunci: Audio Watermarking, CPT, DCT, QIM, QR ABSTRACTAudio watermarking is a technique for inserting information into an audio file and to protect the copyright of digital data from illegal distribution. This paper introduces a stereo audio watermarking based on Quantization Index Modulation (QIM) with combined technique Discrete Cosine Transform (DCT) – QR – Cartesian Polar Transform (CPT). Each frame of a host audio is transformed by DCT, then DCT output is decomposed using QR method. Next, CPT transform two cartesian coefficients from triangular matrix (R) in position (1,1) and (2,2) to polar coefficients. After that, embedding is executed on polar coefficients by QIM. The simulation result shows that the imperceptibility is good with Signal to Noise Ratio (SNR)>20, Mean Opinion Score (MOS)>4 and it is robust against attacks such as Low Pass Filter (LPF) and Band Pass Filter (BPF) with cut off 25-6k, Resampling, Linear Speed Change and MP3 Compression with rate 64 kbps and above. Keywords: Audio Watermarking, CPT, DCT, QIM, QR
Compressive Sensing Audio Watermarking dengan Metode LWT dan QIM SAFITRI, IRMA; IBRAHIM, NUR; YOGASWARA, HERLAMBANG
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 6, No 3 (2018): ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v6i3.405

Abstract

ABSTRAKPenelitian ini mengembangkan teknik Compressive Sensing (CS) untuk audio watermarking dengan metode Lifting Wavelet Transform (LWT) dan Quantization Index Modulation (QIM). LWT adalah salah satu teknik mendekomposisi sinyal menjadi 2 sub-band, yaitu sub-band low dan high. QIM adalah suatu metode yang efisien secara komputasi atau perhitungan watermarking dengan menggunakan informasi tambahan. Audio watermarking dilakukan menggunakan file audio dengan format *.wav berdurasi 10 detik dan menggunakan 4 genre musik, yaitu pop, classic, rock, dan metal. Watermark yang disisipkan berupa citra hitam putih dengan format *.bmp yang masing-masing berukuran 32x32 dan 64x64 pixel. Pengujian dilakukan dengan mengukur nilai SNR, ODG, BER, dan PSNR. Audio yang telah disisipkan watermark, diuji ketahanannya dengan diberikan 7 macam serangan berupa LPF, BPF, HPF, MP3 compression, noise, dan echo. Penelitian ini memiliki hasil optimal dengan nilai SNR 85,32 dB, ODG -8,34x10-11, BER 0, dan PSNR ?.Kata kunci: Audio watermarking, QIM, LWT, Compressive Sensing. ABSTRACTThis research developed Compressive Sensing (CS) technique for audio watermarking using Wavelet Transform (LWT) and Quantization Index Modulation (QIM) methods. LWT is one technique to decompose the signal into 2 sub-bands, namely sub-band low and high. QIM is a computationally efficient method or watermarking calculation using additional information. Audio watermarking was done using audio files with *.wav format duration of 10 seconds and used 4 genres of music, namely pop, classic, rock, and metal. Watermark was inserted in the form of black and white image with *.bmp format each measuring 32x32 and 64x64 pixels. The test was done by measuring the value of SNR, ODG, BER, and PSNR. Audio that had been inserted watermark was tested its durability with given 7 kinds of attacks such as LPF, BPF, HPF, MP3 Compression, Noise, and Echo. This research had optimal result with SNR value of 85.32 dB, ODG value of -8.34x10-11, BER value of 0, and PSNR value of ?.Keywords: Audio watermarking, QIM, LWT, Compressive Sensing.
Audio Watermarking Combined with Compressive Sampling Based on QIM and DST-QR Techniques Safitri, Irma; Budiman, Gelar; Meiza Putri, Arfidianti Kartika
Jurnal Elektronika dan Telekomunikasi Vol 19, No 1 (2019)
Publisher : Indonesian Institute of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/jet.v19.20-25

Abstract

Abuse is not only done to copy or distribute data but also to the digital copyright labels. There is a way to protect data by inserting or hiding a piece of certain information, namely a watermarking technique. In this paper, we propose audio watermarking with Quantization Index Modulation (QIM) method as an embedding process combined with Compressive Sampling (CS), Discrete Sine Transform (DST) and QR decomposition. Binary image is used as a watermark inserted in host audio. DST is used for transformation process from time domain to frequency domain, while QR is used to decompose onedimension matrix into two-dimension matrix. Meanwhile, CS is used to obtain the compressed watermark file which is done before the embedding process. QIM method is used to embed the watermark file to the audio host file. Simulation results indicated that the proposed audio watermarking technique has good robustness against some attacks such as Low Pass Filter (LPF), resampling and linear speed change. In addition, it provides good performance in terms of imperceptibility with Signal to Noise Ratio (SNR) > 20 dB and capacity C = 689 bps.
IMAGE WATERMARKING PADA CITRA MEDIS MENGGUNAKAN COMPRESSIVE SENSING BERBASIS STATIONARY WAVELET TRANSFORM HAFIZHANA, YASQI; SAFITRI, IRMA; NOVAMIZANTI, LEDYA; IBRAHIM, NUR
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 1 (2020): ELKOMIKA
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i1.43

Abstract

ABSTRAK Watermarking pada citra medis dilakukan untuk melindungi hak kepemilikan dan keaslian sebuah citra medis. Proses embedding dan extraction dirancang menggunakan metode Stationary Wavelet Transform (SWT) dan Statistical Mean Manipulation (SMM) untuk mengubah citra host menjadi sinyal sparse kemudian memasuki proses watermarking. Citra watermark dioptimasi dengan menggunakan metode Compressive Sensing (CS). Hasil akhir dari penelitian ini menunjukkan simulasi Image Watermarking dengan Bit Error Rate (BER) mendekati nilai nol dan PSNR lebih besar dari 40 dB, tanpa diberikan serangan. Penerapan Compressive Sensing menyebabkan nilai PSNR meningkat hingga 3,5 dB dan embedding capacity menjadi empat kali lipat lebih baik. Kata Kunci: Image watermarking, Telemedicine, Stationary Wavelet Transform, Statistical Mean Manipulation, Compressive Sensing. ABSTRACT Watermarking in medical images is carried out to protect ownership rights and authenticity of a medical image. The embedding and extraction process was designed using Stationary wavelet transform (SWT) and Statistical Mean Manipulation (SMM) methods to convert the host image into a sparse signal and then enter the watermarking process. The watermark image is optimized using the Compressive Sensing (CS) method. The final result of this final project shows the simulation of Image Watermarking with the Bit Error Rate (BER) approaching zero and PSNR greater than 40 dB, without being given an attack. The application of the Compressive Sensing pursuit will cause the PSNR increase up to 3.5 dB and embedding capacity four times better. Keywords: Image watermarking, Telemedicine, Stationary Wavelet Transform, Statistical Mean Manipulation, Compressive Sensing.
Watermarking berbasis Redundant Discrete Wavelet Transform dan Arnold Transform pada Citra Medis Novamizanti, Ledya; Safitri, Irma; Arindaka, Hafizhan Bhamakerti; Tritoasmoro, Iwan Iwut
Jurnal Teknik Elektro Vol 13, No 2 (2021): Jurnal Teknik Elektro
Publisher : Jurusan Teknik Elektro, Fakultas Teknik, Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jte.v13i2.31691

Abstract

In telemedicine, data transmission in digital medical images and electronic medical records through the internet is vulnerable to various threats of theft and manipulation. Image watermarking is needed to provide authentication and security to medical images. This paper proposes an image watermarking scheme based on Redundant Discrete Wavelet Transform (RDWT) and Discrete Cosine Transform (DCT) with watermark encryption using Arnold transform. First, the original host medical image was decomposed into four subbands using RDWT. Then, DCT is applied to the LH subband of the RDWT. On the other hand, the watermark is scrambled using Arnold transform to ensure identity security. The singular value of the watermarked image is obtained by modifying the singular value of the host image and the watermark. Tests were carried out on different medical images, namely X-ray, MRI, CT, and ultrasound, with a watermark in a proprietary logo. The host medical image is the same size as the watermark image. The result of this study can provide high authentication, imperceptibility and security in medical images, with an average PSNR value of 65.67 dB, SSIM 1, BER 0, NC 1. This scheme is resistant to JPEG compression, noise addition, filtering, image sharpening, image enhancement, geometric operations, motion blur, image sharpening, and histogram equalization.
Modified DCT-based Audio Watermarking Optimization using Genetics Algorithm Ledya Novamizanti; Gelar Budiman; Irma Safitri
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.10111

Abstract

Ease process digital data information exchange impact on the increase in cases of copyright infringement. Audio watermarking is one solution in providing protection for the owner of the work. This research aims to optimize the insertion parameters on Modified Discrete Cosine Transform (M-DCT) based audio watermarking using a genetic algorithm, to produce better audio resistance. MDCT is applied after reading host audio, then embedding in MDCT domain is applied by Quantization Index Modulation (QIM) technique. Insertion within the MDCT domain is capable of generating a high imperceptible watermarked audio due to its overlapping frame system. The system is optimized using genetic algorithms to improve the value of imperceptibility and robustness in audio watermarking. In this research, the average SNR reaches 20 dB, and ODG reaches -0.062. The subjective quality testing on the system obtains an average MOS of 4.22 out of five songs tested. In addition, the system is able to withstand several attacks. The use of M-DCT in audio watermaking is capable of producing excellent imperceptibility and better watermark robustness.
Audio Watermarking Combined with Compressive Sampling Based on QIM and DST-QR Techniques Irma Safitri; Gelar Budiman; Arfidianti Kartika Meiza Putri
Jurnal Elektronika dan Telekomunikasi Vol 19, No 1 (2019)
Publisher : LIPI Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/jet.v19.20-25

Abstract

Abuse is not only done to copy or distribute data but also to the digital copyright labels. There is a way to protect data by inserting or hiding a piece of certain information, namely a watermarking technique. In this paper, we propose audio watermarking with Quantization Index Modulation (QIM) method as an embedding process combined with Compressive Sampling (CS), Discrete Sine Transform (DST) and QR decomposition. Binary image is used as a watermark inserted in host audio. DST is used for transformation process from time domain to frequency domain, while QR is used to decompose onedimension matrix into two-dimension matrix. Meanwhile, CS is used to obtain the compressed watermark file which is done before the embedding process. QIM method is used to embed the watermark file to the audio host file. Simulation results indicated that the proposed audio watermarking technique has good robustness against some attacks such as Low Pass Filter (LPF), resampling and linear speed change. In addition, it provides good performance in terms of imperceptibility with Signal to Noise Ratio (SNR) > 20 dB and capacity C = 689 bps.
IMPLEMENTATION OF QIM BASED AUDIO WATERMARKING USING HYBRID TRANSFORM OF SWT-DCT-SVD METHODS OPTIMIZED WITH GENETIC ALORITHM Ryan Aminullah; Gelar Budiman; Irma Safitri
TEKTRIKA Vol 2 No 1 (2017): TEKTRIKA Vol.2 No.1 2017
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/tektrika.v2i1.1661

Abstract

Nowadays, almost all data transaction is done through the internet because it is easy and could be accessed anywhere. The file is uploaded directly without any security or scanning making people able to upload illegal files or files that is not owned by them. This violation of copyright becomes a huge problem as it reduces the owner’s profit. That is why watermarking method is created. Watermarking is a method of embedding secret information to a host data. The information could be embedded into an audio, image or video data. This research will design an audio watermarking by combining 3 methods of transformation: Stationary Wavelet Transform (SWT), Discrete Cosine Transform (DCT), and Singular Value Decomposition (SVD). SWT separates data’s frequency into high and low. After that, DCT maps correlated high frequency data into uncorrelated coefficient. Then those coefficients will be deconstructed into three matrices u, s, and v using SVD method. Later, the s matric will be embedded with the watermark. With these methods, watermarked audio produce SNR>20dB and BER≈0,1170 in average.
Perancangan Dan Analisis Audio Watermarking Berbasis Discrete Sine Transform (dst) Dengan Metode Lifting Wavelet Transform (lwt) Dan Centroid Muhammad Aprianda Rahmadi; Gelar Budiman; Irma Safitri
eProceedings of Engineering Vol 5, No 1 (2018): April 2018
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penyebaran informasi dan data digital terutama lagu di internet telah berdampak negatif terhadap perlindungan hak cipta dari lagu tersebut. Untuk melindungi hak cipta pada lagu tersebut, maka di perlukan suatu teknik yang tidak hanya handal, namun tahan terhadap berbagai serangan yaitu teknik audio watermarking. Pada paper ini, dilakukan perancangan dan analisis audio watermarking dengan menggabungkan beberapa metode seperti Discrete Sine Transform (DST), Lifting Wavelet Transform (LWT), dan Centroid. Di metode LWT, Host audio akan di segmentasi melalui dua filter yaitu High Pass Filter (HPF) dan Low Pass Filter (LPF). Setelah itu, host akan di osilasi dengan fungsi sinus amplituda dan frekuensi yang berbeda-beda sehingga korelasi unsur-unsur dari sinyal dapat dihilangkan dan diperoleh sinyal dalam domain frekuensi. Metoda Centroid, digunakan untuk mencari nilai amplituda titik pusat dari sinyal, setalah mendapatkan titik pusat dari centroid lalu watermark disisipkan dengan mengubah titik pusat nya menggunakan teknik QIM. Hasil penelitian ini, menunjukkan bahwa sistem audio watermarking yang dirancang memiliki parameter robustness yang baik terhadap serangan LPF, BPF (25-6k), Resampling, TSM, LSC, Kompresi MP3, dan kompresi MP4 dimana BER yang diperoleh <10 %. Memiliki kapasitas watermark yang besar yaitu 689,0625 bps, dan nilai SNR 24 dB.