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Iwan Iwut

Bio: Iwan Iwut is an academic researcher from Telkom University. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 3, co-authored 5 publications receiving 30 citations.

Papers
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Journal ArticleDOI
TL;DR: The simulation result performs that GA is useful to search the value of parameter that produces controllable the combination between robustness, invisibility and capacity, and improves the method by determining the exactvalue of parameter achieving BER, PSNR and payload.
Abstract: data in an image file is needed by its owner to set his ownership in a logo as a watermark embedded in the image file. Hiding the logo in the image was done in several methods. One of the method is domain transform using 2D-DCT in which data is embedded in frequency domain of the image. First, the host RGB image is converted to certain color space. The available and chosen color spaces are RGB, YCbCr or NTSC. The layer in which the watermark is embedded also can be selected. The available choices are 1 st layer, 2 nd layer, 3 rd layer, 1 st & 2 nd layer, 2 nd & 3 rd layer, 1 st & 3 rd layer and all layers. After the selected layer of image in certain color space is transformed in block based to frequency domain by DCT, one bit watermark is embedded on the AC coefficient of each block such a way that the bit is represented by specific value called delta in a zigzag and vary length of pixel. The vary parameters optimized by Genetics Algorithm are selected color space, selected layer, block size, length of pixel to be embedded by one bit watermark, and delta. Bit “1” is represented by +delta, and bit “0” is represented by –delta in vary length of pixel after zigzag. The simulation result performs that GA is useful to search the value of parameter that produces controllable the combination between robustness, invisibility and capacity. Thus, GA improves the method by determining the exact value of parameter achieving BER, PSNR and payload.

16 citations

Journal ArticleDOI
01 Jan 2017
TL;DR: Robustness in the proposed method has reached perfect watermark quality with BER=0.01, and the watermark image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.
Abstract: Data hiding in an image content is mandatory for setting the ownership of the image. Two dimensions discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed as transform method in this paper. First, the host image in RGB color space is converted to selected color space. We also can select the layer where the watermark is embedded. Next, 2D-DWT transforms the selected layer obtaining 4 subband. We select only one subband. And then block-based 2D-DCT transforms the selected subband. Binary-based watermark is embedded on the AC coefficients of each block after zigzag movement and range based pixel selection. Delta parameter replacing pixels in each range represents embedded bit. +Delta represents bit "1" and –delta represents bit "0". Several parameters to be optimized by Genetics Algorithm (GA) are selected color space, layer, selected subband of DWT decomposition, block size, embedding range, and delta. The result of simulation performs that GA is able to determine the exact parameters obtaining optimum imperceptibility and robustness, in any watermarked image condition, either it is not attacked or attacked. DWT process in DCT based image watermarking optimized by GA has improved the performance of image watermarking. By five attacks: JPEG 50%, resize 50%, histogram equalization, salt-pepper and additive noise with variance 0.01, robustness in the proposed method has reached perfect watermark quality with BER=0. And the watermarked image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.

14 citations

01 Aug 2017
TL;DR: Tugas akhir in this paper membahas mengenai pengenalan pembicara (speaker recognition), yaitu mekanisme pengenealan identitas subjek berdasarkan ciri suaranya.
Abstract: Tugas akhir ini membahas mengenai pengenalan pembicara (speaker recognition), yaitu mekanisme pengenalan identitas subjek berdasarkan ciri suaranya. Pertama, sinyal suara subjek yang diuji diekstraksi cirinya menggunakan metode MFCC (Mel Frequency Cepstrum Coefficient). Tahapan di dalam MFCC termasuk diantaranya adalah pre-emphasis, framing, windowing, FFT (Fast Fourier Transform), mel scaling dan DCT (Discrete Cosine Transform), yang mana keluaran MFCC adalah feature vector yang dinamakan cepstrum. Selanjutnya, cepstrum dari masing-masing subjek akan dimodelkan menggunakan metode GMM (Gaussian Mixture Model). Tahapan di dalam GMM termasuk diantaranya adalah Expectation-step dan Maximization-step, yang mana keluaran GMM adalah distribusi Gaussian dengan parameter mean (µ) dan variance ( ) yang unik untuk masingmasing subjek. Proses klasifikasi dilakukan dengan membandingkan parameter distribusi Gaussian antara data latih dan data uji. Pada penelitian internasional sebelumnya oleh kelompok mahasiswa di Preston University dan Jinnah Women University, Pakistan, dengan judul “Speaker Identification Using GMM with MFCC” diperoleh akurasi sebesar 87.5% dengan metode ekstraksi ciri MFCC, metode clustering K-Means, metode modelling GMM dan diklasifikasikan menggunakan log probability. Pada tugas akhir ini, kita akan melewatkan tahap clustering dan tahap klasifikasi dilakukan dengan melakukan perbandingan pada distribusi Gaussian memanfaatkan parameter mean (µ) dan variance ( ), dimana merupakan cara paling cepat dan mudah. Pada tugas akhir ini, diusahakan akurasi yang didapat mampu mendekati penelitian yang sudah ada mengingat tahap klasifikasi yang digunakan bisa dikatakan cara ‘kasar’ dalam penggunaan Gaussian Mixture Model (GMM) sehingga tidak bisa diekspektasikan lebih baik, meskipun banyak faktor lain yang bisa mempengaruhi akurasi simulasi. Kata kunci: Speaker recognition, Mel Frequency Cepstrum Coefficient (MFCC), Gaussian Mixture Model (GMM), Expectation Maximization (EM)

7 citations

Proceedings ArticleDOI
01 Aug 2015
TL;DR: A novel method of cryptography, “Horse Step Algorithm” is proposed, which exploits 2 dimensional matrix for scrambling message bit by bit and two kind of keys are proposed to make it more secure.
Abstract: Cryptography is the art and science of securing message so unintended audiences cannot read, understand, or alter the message. Some of cryptography that has been proposed such as DES, 3DES, and AES use mathematical operation to scramble block or part of block message to encrypt. The important thing to secure message in cryptography is a key. They use variable fixed-length of key to keep the security of message. We propose novel method of cryptography, “Horse Step Algorithm”. Such algorithm exploits 2 dimensional matrix for scrambling message bit by bit. We propose two kind of keys to make it more secure. The key that we are proposing are flexible and very easy to make which can be in the form of numbers, texts, or sentences. It is very easy to make a key. By implementing this algorithm, we get flexibility of the key and excellent security. In Analysis we compare it with RSA, DES, 3DES and AES algorithm.

2 citations

Proceedings ArticleDOI
30 Nov 2015
TL;DR: Simulation results confirm that PS-OFDM technique offer a fine performance, where minimum BER achieved on 22 dB up to 24 dB of SNR, and maximum data rate, achieved for 16-QAM mapper by 1/16 guard interval, is confirmed.
Abstract: Various of multicarrier modulation scheme may be used to bit rate increases of Broadband PLC channel. One of the schemes is the Pulse-Shaped OFDM (PS-OFDM). There is an important parameter in the PS-OFDM that influence the increasing in bit rate on the PLC channel, the guard interval, and the number of subchannels. This paper discusses performance of the system against the effects of code rate, multipath propagation channel on Broadband PLC channel, and the effect of the guard interval of data transmission speed. Simulation results confirm that PS-OFDM technique offer a fine performance, where minimum BER achieved on 22 dB up to 24 dB of SNR, and maximum data rate on 41,033 Mbps, achieved for 16-QAM mapper by 1/16 guard interval.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: The proposed AES algorithm for cryptography and DWT for steganography is implemented and Huffman Coding is proposed to reduce the total of the message’s bit and increase the capacity.
Abstract: Information security is very important and has been widely implemented. Cryptography and steganography are two common methods that can be implemented to secure and conceal the information. In this research, the proposed AES algorithm for cryptography and DWT for steganography. However, in case of implementing DWT as steganography, there is a weakness which is a lower capacity. Based on DWT’s problem, proposed Huffman Coding to reduce the total of the message’s bit and increase the capacity. In the implementation, a message will be processed by using AES and compressed by using Huffman Coding then conceal in a cover using DWT. After doing several experiments using a 128x128 pixel message image and a 512x512 pixel of the cover image, achieved the average of MSE is 1.5676 and the average of PSNR result is above 40db which is 46.1878.

24 citations

Journal ArticleDOI
01 Jan 2017
TL;DR: Robustness in the proposed method has reached perfect watermark quality with BER=0.01, and the watermark image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.
Abstract: Data hiding in an image content is mandatory for setting the ownership of the image. Two dimensions discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed as transform method in this paper. First, the host image in RGB color space is converted to selected color space. We also can select the layer where the watermark is embedded. Next, 2D-DWT transforms the selected layer obtaining 4 subband. We select only one subband. And then block-based 2D-DCT transforms the selected subband. Binary-based watermark is embedded on the AC coefficients of each block after zigzag movement and range based pixel selection. Delta parameter replacing pixels in each range represents embedded bit. +Delta represents bit "1" and –delta represents bit "0". Several parameters to be optimized by Genetics Algorithm (GA) are selected color space, layer, selected subband of DWT decomposition, block size, embedding range, and delta. The result of simulation performs that GA is able to determine the exact parameters obtaining optimum imperceptibility and robustness, in any watermarked image condition, either it is not attacked or attacked. DWT process in DCT based image watermarking optimized by GA has improved the performance of image watermarking. By five attacks: JPEG 50%, resize 50%, histogram equalization, salt-pepper and additive noise with variance 0.01, robustness in the proposed method has reached perfect watermark quality with BER=0. And the watermarked image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.

14 citations

Journal ArticleDOI
TL;DR: The proposed scheme demonstrates that the watermark recovery from chrominance blue was resistant against different types of attacks and the tradeoff between normalize cross-correlation and imperceptibility of watermarked image from quantization steps was used to achieve an optimal threshold value.
Abstract: Digital watermarking is an alternative solution to prevent unauthorized duplication, distribution and breach of ownership right. This paper proposes a watermarking scheme for multiple watermarks embedding. The embedding of multiple watermarks use a block-based scheme based on human visual characteristics. A threshold is used to determine the watermark values by modifying first column of the orthogonal U matrix obtained from Singular Value Decomposition (SVD). The tradeoff between normalize cross-correlation and imperceptibility of watermarked image from quantization steps was used to achieve an optimal threshold value. The results show that our proposed multiple watermarks scheme exhibit robustness against signal processing attacks. The proposed scheme demonstrates that the watermark recovery from chrominance blue was resistant against different types of attacks.

14 citations

Proceedings ArticleDOI
01 Nov 2018
TL;DR: This project will be done speaker recognition technique (Speaker Recognition) to be able to classify the speaker’s voice in the evidence and the voice of the suspect, using the Learning Vector Quantization Neural Network method.
Abstract: Presently, Biometric features are often used to identify suspects in law enforcement processes. One of these biometric features is Speaker Recognition. Speaker recognition is used to discriminate people by their voice. In this study, the problem that can be solved is how to classify audio sample that exist on the evidence with the voice of the suspect.In this final project is made a application’s prototype that can be used to classify and in that case will be done speaker recognition technique (Speaker Recognition) to be able to classify the speaker’s voice in the evidence and the voice of the suspect. The stages used to compare the sound is by extracting the sound features using the Mel-frequency Cepstral Coefficients (MFCC) method and using the Learning Vector Quantization Neural Network (JST-LVQ) method as the classification method of the voice extraction result.By using LVQ, the accuracy in recognition the speaker’s voice is pretty good. The use of LVQ method produces best accuracy at 73,33% to recognize the speaker that with the same sentence, and 46,67% for different sentence. So the results obtained in accordance with the expected.

11 citations