IMPLEMENTASI AUDIO WATERMARKING MENGGUNAKAN DISCRETE COSINE TRANSFORM (DCT) IMPLEMENTATION OF AUDIO WATERMARKING USING DISCRETE COSINE TRANSFORM (DCT)

ABSTRAKSI: Watermarking merupakan suatu teknik untuk menyembunyikan suatu data digital pada data digital yang lain. Salah satu implementasi watermarking adalah audio watermarking. Teknologi watermarking pada data audio digital terbagi menjadi dua, yaitu temporal watermarking, menyembunyikan watermark langsung ke dalam audio dalam domain waktu dan spectral watermarking, adanya proses transformasi dari domain waktu ke domain frekuensi. Transformasi yang biasa digunakan misalnya DCT, FFT, DWT, dll. Namun pengimplementasian metode transformasi DCT dalam audio watermarking masih jarang dijumpai. Dalam tugas akhir ini diimplementasikan teknik audio watermarking, yaitu teknik menyisipkan suatu data digital berupa teks ke dalam file audio digital yang berformat *.wav dengan menggunakan transformasi DCT (Discrete Cosine Transform). Terhadap audio terwatermark dilakukan pengujian kualitas secara obyektif dan subyektif serta diadakan pengujian ketahanan watermark terhadap beberapa proses pengolahan sinyal. Dari pengujian yang telah dilakukan secara obyektif dan subyektif terhadap sistem audio watermarking menggunakan DCT diperoleh hasil bahwa audio terwatermark mempunyai kualitas menyerupai file audio aslinya bila nilai SNR yang dihasilkan diatas 78,538 dB dan kualitas audio watermark tergantung nilai koefisien pengali dan panjang teks. Hasil pengujian menunjukkan bahwa nilai koefisien pengali 0,001 menghasilkan kualitas audio terwatermark yang mendekati aslinya. Sedangkan dari pengujian ketahanan watermark terhadap pengolahan sinyal didapatkan bahwa dalam sistem audio watermarking menggunakan DCT, tingkat ketahanan watermark berupa teks sangat rentan terhadap perubahan.Kata Kunci : Audio Watermarking, Discrete Cosine TransformABSTRACT: Watermarking is technique to hide a digital data into another digital data. Audio watermarking is an implementation of watermarking. Digital audio watermarking technology consist of temporal watermarking which is directly hide watermark into audio on time domain and spectral watermarking which is use transformation from time domain into frequency domain. Commonly used transformations are DCT, FFT, DWT, etc. However implementation of employing the DCT method for audio watermarking still rare to meet. Audio watermarking a technique to embed digital data (in this case text) into digital audio file (WAV extension) was implemented on this thesis using Discrete Cosine Transform (DCT). Objective and subjective quality test was conducted into watermarked audio. Watermark robustness test against some digital signal processing also conducted. From objective and subjective test result to DCT based audio watermarking system, I conclude that watermarked audio have almost equal quality compared to original audio file if SNR resulted is above 78,538 dB and watermarked audio quality depend on multiplier coefficient and the text length. Test result show that on multiplier coefficient 0,001 quality of audio file close to it’s original. Meanwhile from watermark robustness test against digital signal processing I conclude that on DCT based audio watermarking system, robustness level on text watermark is very susceptible with alteration.Keyword: Audio Watermarking, Discrete Cosine Transfor

A robust digital image watermarking using repetition codes against common attacks

Digital watermarking is hiding the information inside a digital media to protect for such documents against malicious intentions to change such documents or even claim the rights of such documents. Currently the capability of repetition codes on various attacks in not sufficiently studied. In this project, a robust frequency domain watermarking scheme has been implemented using Discrete Cosine Transform (DCT). The idea of this scheme is to embed an encoded watermark using repetition code (3, 1) inside the cover image pixels based on Discrete Cosine Transform (DCT) embedding technique. The proposed methods have undergone several simulation attacks tests in order to check up and compare their robustness against various attacks, like salt and pepper, speckle, compress, Gaussian, image contrast, resizing and cropping attack. The robustness of the watermarking scheme has been calculated using Peak Signal-To-Noise Ratio (PSNR), Mean Squared Error (MSE) and Normalized Correlations (NC). In our experiments, the results show that the robustness of a watermark with repetition codes is much better than without repetition code

Progressive Pattern Matching Approach Using Discrete Cosine Transform

Abstract-The discrete cosine transform (DCT) i

Reduced Multiplicative Complexity Discrete Cosine Transform (DCT) Circuitry

System and techniques for reduced multiplicative complex­ity discrete cosine transform (DCT) circuitry are described herein. An input data set can be received and, upon the input data set, a self-recursive DCT technique can be performed to produce a transformed data set. Here, the self-recursive DCT technique is based on a product of factors of a specified type of DCT technique. Recursive components of the technique are of the same DCT type as that of the DCT technique. The transformed data set can then be produced to a data con­sumer

Image Restoration Effect on DCT High Frequency Removal and Wiener Algorithm for Detecting Facial Key Points

This study aims to figure out the effect of using Histogram Equalization and Discrete Cosine Transform (DCT) in detecting facial keypoints, which can be applied for 3D facial reconstruction in face recognition. Four combinations of methods comprising of Histogram Equalization, removing low-frequency coefficients using Discrete Cosine Transform (DCT) and using five feature detectors, namely: SURF, Minimum Eigenvalue, Harris-Stephens, FAST, and BRISK were used for test. Data that were used for test were obtained from Head Pose Image and ORL Databases. The result from the test were evaluated using F-score. The highest F-score for Head Pose Image Dataset is 0.140 and achieved through the combination of DCT & Histogram Equalization with feature detector SURF. The highest F-score for ORL Database is 0.33 and achieved through the combination of DCT & Histogram Equalization with feature detector BRISK

The Effect of Using Histogram Equalization and Discrete Cosine Transform on Facial Keypoint Detection

This study aims to figure out the effect of using Histogram Equalization and Discrete Cosine Transform (DCT) in detecting facial keypoints, which can be applied for 3D facial reconstruction in face recognition. Four combinations of methods comprising of Histogram Equalization, removing low-frequency coefficients using Discrete Cosine Transform (DCT) and using five feature detectors, namely: SURF, Minimum Eigenvalue, Harris-Stephens, FAST, and BRISK were used for test. Data that were used for test were obtained from Head Pose Image and ORL Databases. The result from the test were evaluated using F-score. The highest F-score for Head Pose Image Dataset is 0.140 and achieved through the combination of DCT & Histogram Equalization with feature detector SURF. The highest F-score for ORL Database is 0.33 and achieved through the combination of DCT & Histogram Equalization with feature detector BRISK

Keamanan Pesan Rahasia Menggunakan Steganografi DCT (Discrete Cosine Transform) pada Citra JPEG

Abstract The  least significant-bit (LSB) based techniques are very popular for steganography in spatial domain. The simplest LSB technique simply replaces the LSB in the cover image with the  bits from secret information. Further advanced techniques use some criteria to identify the pixels in which LSB(s) can be replaced with the bits of secret information. In Discrete Cosine Transform (DCT) based technique insertion of secret information in carrier depends on the DCT coefficients. Any DCT coefficient value above proper threshold is a potential place for insertion of secret information. Keywords : Discrete Cosine Transform (DCT), steganography, secret message AbstrakPada steganografi domain spasial, teknik least significant-bit (LSB) merupakan teknik yang paling banyak digunakan pada steganografi. Teknik yang sederhana yang hanya mengubah nilai LSB pada cover image dengan nilai bit pesan rahasia, atau dengan teknik yang lebih baik lagi yaitu dengan menentukan bit-bit LSB mana yang akan dilakukan pergantian nilai bit. Lain halnya dengan metode Discrete Cosine Transform (DCT), teknik steganografi ini akan menyembunyikan informasi rahasia tergantung dari nilai Koefisien DCT. Kata Kunci : Steganografi, DCT, Citra, JPEG, Pesan Rahasi