• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.403-413
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• 2011

In this paper, we proposed a digital image watermarking technique using scrambled binary phase computer generated hologram in the discrete cosine transform(DCT) domain. For the embedding process of watermark. Using simulated annealing algorithm, we would generate a binary phase computer generated hologram(BPCGH) which can reconstruct hidden image perfectly instead of hidden image and encrypt it through the scramble operation. We multiply the encrypted watermark by the weight function and embed it into the DC coefficients in the DCT domain of host image and an inverse DCT is performed. For the extracting process of watermark, we compare the DC coefficients of watermarked image and original host image in the DCT domain and dividing it by the weight function and decrypt it using descramble operation. And we recover the hidden image by inverse Fourier transforming the decrypted watermark. Finally, we compute the correlation between the original hidden image and recovered hidden image to determine if a watermark exits in the host image. The proposed watermarking technique use the hologram information of hidden image which consist of binary values and scramble encryption technique so it is very secure and robust to the various external attacks such as compression, noises and cropping. We confirmed the advantages of the proposed watermarking technique through the computer simulations.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.12-26
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• 2000

In this paper, we propose a post-processing algorithm to remove false minutiae which decrease the overall performance of an automatic fingerprint identification system by increasing computational complexity, FAR(False Acceptance Rate), and FRR(False Rejection Rate) in matching process. The proposed algorithm extracts candidate minutiae from thinned fingerprint image. Considering characteristics of the thinned fingerprint image, the algorithm selects the minutiae that may be false and located in recoverable area. If the area where the selected minutiae reside is thinned incorrectly due to noise and loss of information, the algorithm recovers the area and the selected minutiae are removed from the candidate minutiae list. By examining the ridge pattern of the block where the candidate minutiae are found, true minutiae are recovered and in contrast, false minutiae are filtered out. In an experiment, Fingerprint images from NIST special database 14 are tested and the result shows that the proposed algorithm reduces the false minutiae extraction rate remarkably and increases the overall performance of an automatic fingerprint identification system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.87-95
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• 2013

In this paper, 2.5 Gb/s burst-mode clock and data recovery(CDR) is presented. Digital frequency calibration scheme is adopted to eliminate mismatch between the input data rate and the output frequency of the gated voltage controlled oscillator(GVCO) in the clock recovery circuitry. A jitter rejection scheme is also used to reduce jitter caused by input data. The proposed burst-mode CDR is designed using 0.11 ${\mu}m$ CMOS technology. Post-layout simulations show that peak-to-peak jitter of the recovered data is 14 ps with 0.1 UI input referred jitter, and maximum tolerance of consecutive identical digit(CID) is 2976 bits without input data jitter. The active area occupies 0.125 $mm^2$ without loop filter and the total power consumption is 94.5 mW.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2027-2035
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• 2001

In this paper, we present an audio stream delivery using the AMR (Adaptive Multi-Rate) coder that was adopted by ETSI and 3GPP as a standard vocoder for next generation IMT-2000 service in which includes combined sender (FEC) and receiver reconstruction technique in the Internet. By use of the media-specific FEC scheme, the possibility to recover lost packets can be much increased due to the addition of repair data to a main data stream, by which the contents of lost packets can be recovered. The AMR codec is based on the code-excited linear predictive (CELP) coding model. So we use a frame erasure concealment for CELP-based coders. The proposed scheme is evaluated with ITU-T G.729 (CS-ACELP) coder and AMR - 12.2 kbit/s through the SNR (Signal to Noise Ratio) and the MOS (Mean Opinion Score) test. The proposed scheme provides 1.1 higher in Mean Opinion Score value and 5.61 dB higher than AMR - 12.2 kbit/s in terms of SNR in 10% packet loss, and maintains the communicab1e quality speech at frame erasure rates lop to 20%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12B
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• pp.1371-1379
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• 2009

In this paper, we propose a new multi-path routing protocol to provide reliable and stable data transmission in MANET that is composed of high-mobility nodes. The new multi-path routing establishes the main route by the mechanism based on AODV, and then finds the backup route that node-disjoint from the main route by making add nodes in the main route not participate in it. The data transmission starts immediately after finding the main route. And the backup route search process is taking place while data is transmitted to reduce the transmission delay. When either of the main route or the backup route is broken, data is transmitted continuously through the other route and the broken route is recovered to node-disjoint route by the route maintenance process. The result of the simulation based on the Qualnet simulator shows that the backup route exists 62.5% of the time when the main route is broken. And proposed routing protocol improved the packet transmission rate by 2~3% and reduced the end-to-end delay by 10% compared with AODV and AODV-Local Repair.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.5
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• pp.486-492
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• 2004

In this paper, we newly propose the binary CA-CDMA(constant amplitude CDMA) system using pre-coding method to solve the high PAPR problem caused by multi-user signal transmission in the CDMA system. 4-user CA-CDMA, the basis of proposed binary CA-CDMA system, makes binary output signal for 4 input users. It produces the output of binary(${\pm}$2) amplitude by using a parity signal resulting from the XOR operation of 4 users data. Another sub-channel or more bandwidth is not necessary because it is transmitted together with user data and can be easily recovered in the receiver. The extension of the number of users can be possible by the simple repetition of the basic binary 4-user CA-CDMA. For example, binary 16-user CA-CDMA is made easily by allocating the four 4-user CA-CDMA systems in parallel and leading the four outputs to the fifth 4-user CA-CDMA system as input, because the output signal of each 4-user CA-CDMA is also binary. By the same extension procedure, binary 64 and 256-user CA-CDMA systems can be made with the constant amplitude. As a result, the code rate of this proposed CA-CDMA system is just 1 and binary CA-CDMA does not change the transmission rate with the constant output signal(PAPR = 0 ㏈). Therefore, the power efficiency of the HPA can be maximized without the nonlinear distortion. From the simulation results, it is verified that the conventional CDMA system has multi-level output signal, but the proposed binary CA-CDMA system always produces binary output. And it is also found that the BER of conventional CDMA system is increased by nonlinear HPA, but the BER of proposed binary CA-CDMA system is not changed.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.43-54
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• 2018

Images taken in haze weather are characteristic of low contrast and poor visibility. The process of reconstructing clear-weather image from a hazy image is called dehazing. The main challenge of image dehazing is to estimate the transmission map or depth map for an input hazy image. In this paper, we propose a single image dehazing method by utilizing the Generative Adversarial Network(GAN) for accurate depth map estimation. The proposed GAN model is trained to learn a nonlinear mapping between the input hazy image and corresponding depth map. With the trained model, first the depth map of the input hazy image is estimated and used to compute the transmission map. Then a guided filter is utilized to preserve the important edge information of the hazy image, thus obtaining a refined transmission map. Finally, the haze-free image is recovered via atmospheric scattering model. Although the proposed GAN model is trained on synthetic indoor images, it can be applied to real hazy images. The experimental results demonstrate that the proposed method achieves superior dehazing results against the state-of-the-art algorithms on both the real hazy images and the synthetic hazy images, in terms of quantitative performance and visual performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.392-400
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• 2001

This paper proposes an illuminant estimation algorithm that estimates the spectral power distribution of an incident light source from a single image. The proposed illumination recovery procedure has two phases. First, the surface spectral reflectances are recovered in the maximum achromatic region (MAR) which is the most achromatic and highly bright region of an image after removing partially the effect of illumination using a modified gray world algorithm. Here, the surface reflectances of MAR are estimated using the principal component analysis method along with a set of given 1269 Munsell samples. Second, the Population of reflected lights is determined with 1269 Munsell samples and a set of illuminations then the spectral distribution of re(looted lights of MAR is selected from the spectral database. That is, color differences are compared between the reflected lights of the MAR and the spectral database, which is the set of reflected lights built by the given set of Munsell samples and illuminants. Then the closest colors from the spectral database are selected. Finally, the illuminant of an image can be calculated dividing the average spectral distributions of reflected lights of MAR by the average surface reflectances of the MAR. In order to evaluate the proposed algorithm, experiments with artificial scenes, which are exposed to chromatic illuminants, were performed and the spectral distribution of estimated illumination and color difference are compared with results of the conventional method.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.73-81
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• 2018

The quality of side scan sonar images is determined by the frequency of a sonar. A side scan sonar with a low frequency creates low-quality images. One of the factors that lead to low quality is a high-level noise. The noise is occurred by the underwater environment such as equipment noise, signal interference and so on. In addition, in order to compensate for the transmission loss of sonar signals, the received signal is recovered by TVG (Time-Varied Gain), and consequently the side scan sonar images contain non-homogeneous noise which is opposite to optic images whose noise is assumed as homogeneous noise. In this paper, the SSCS (Structural Sparsity based Compressive Sensing) is proposed for removing non-homogeneous noise. The algorithm incorporates both local and non-local models in a structural feature domain so that it guarantees the sparsity and enhances the property of non-local self-similarity. Moreover, the non-local model is corrected in consideration of non-homogeneity of noises. Various experimental results show that the proposed algorithm is superior to existing method.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.12-20
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• 2018

Efforts have been made to reconstruct low-resolution underwater images to high-resolution ones by using the image SR (Super-Resolution) method, all to improve efficiency when acquiring side-scan sonar images. As side-scan sonar images are similar with the optical images with respect to exploiting 2-dimensional signals, conventional image restoration methods for optical images can be considered as a solution. One of the most typical super-resolution methods for optical image is a sparse coding and there are studies for verifying applicability of sparse coding method for underwater images by analyzing sparsity of underwater images. Sparse coding is a method that obtains recovered signal from input signal by linear combination of dictionary and sparse coefficients. However, it requires huge computational load to accurately estimate sparse coefficients. In this study, a sparse coding based underwater image super-resolution method is applied while a selective reconstruction method for object region is suggested to reduce the processing time. For this method, this paper proposes an edge detection and object and non object region classification method for underwater images and combine it with sparse coding based image super-resolution method. Effectiveness of the proposed method is verified by reducing the processing time for image reconstruction over 32 % while preserving same level of PSNR (Peak Signal-to-Noise Ratio) compared with conventional method.