• The KIPS Transactions:PartB
• /
• v.17B no.3
• /
• pp.197-206
• /
• 2010

High-quality and low-price digital printing devices are nowadays abused to print or forge official documents and bills. Identifying color laser printers will be a step for media forensics. This paper presents a new method to identify color laser printers with printed color images. Since different printer companies use different manufactural systems, printed documents from different printers have little difference in visual. Analyzing this artifact, we can identify the color laser printers. First, high-frequency components of images are extracted from original images with discrete wavelet transform. After calculating the gray-level co-occurrence matrix of the components, we extract some statistical features. Then, these features are applied to train and classify the support vector machine for identifying the color laser printer. In the experiment, total 2,597 images of 7 printers (HP, Canon, Xerox DCC400, Xerox DCC450, Xerox DCC5560, Xerox DCC6540, Konica), are tested to classify the color laser printer. The results prove that the presented identification method performs well with 96.9% accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.3
• /
• pp.71-78
• /
• 2011

This paper propose image steganalysis scheme based on independence between parent and child subband on the multi-layer wavelet domain. The proposed method decompose cover and stego images into 12 subbands by applying 3-level Haar UWT(Undecimated Wavelet Transform), analyze statistical independency between parent and child subband. Because this independency is appeared more difference in stego image than in cover image, we can use it as feature to differenciate between cover and stego image. Therefore we extract 72D features by calculation first 3 order statistical moments from joint characteristic function between parent and child subband. Multi-layer perceptron(MLP) is applied as classifier to discriminate between cover and stego image. We test the performance of proposed scheme over various embedding rates by the LSB, SS, BSS embedding method. The proposed scheme outperforms the previous schemes in detection rate to existence of hidden message as well as exactness of discrimination.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.9B
• /
• pp.1330-1341
• /
• 2010

Power analysis (PA) is known as a powerful physical attack method in the field of information security. This method uses the statistical characteristics of leaked power consumption signals measured from security devices to reveal the secret keys. However, when measuring a leakage power signal, it may be easily distorted by the noise due to its low magnitude values, and thus the PA attack shows different performances depending on the noise level of the measured signal. To overcome this vulnerability of the PA attack, we propose a noise-reduction method based on wavelet de-noising. Experimental results show that the proposed de-noising method improves the attack efficiency in terms of the number of signals required for the successful attack as well as the reliability on the guessing key.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.05c
• /
• pp.2065-2068
• /
• 2003

본 논문은 복합적인 상황을 고려한 데이터를 이용하여 얼굴인식을 하는 연구로서, 이산 웨이블렛을 기반으로 하는 다 해상도 분석 방법을 사용하고, 각 해상도에서 얻어진 계수를 이용하여 LDA와 ICA기법을 융합하는 방법을 제안한다. 기존의 얼굴인식방법은 정면에서 바라본 임의의 얼굴영상을 이용하므로, 예상하지 못한 얼굴 로션 변화에 대한 고려와 빛의 변화에 대해 고려하지 못했었다. 그러나, 본 연구에서는 다양한 상황을 고려한 데이터를 취득하여 해상도 별로 분리된 대역에 FLD와 ICA를 선택적으로 융합한 알고리즘을 적용하므로서 인식율을 높일 수 있었다

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.48 no.6
• /
• pp.82-90
• /
• 2011

This paper proposes an advanced outdoor localization algorithm of a GPS(global positioning system)-INS(inertial navigation system) integration system. In order to reduce noise from the internal INS sensors, discrete wavelet transform and variable threshold method are utilized. The UPF (unscented particle filter) combines GPS information and INS signals to implement precise outdoor localization algorithm and to reduce noise caused by the acceleration, deceleration, and unexpected slips. The conventional de-noising method is mainly carried out using a low pass filter and a high pass filter which essentially result in signal distortions. This newly proposed system utilizes the vibration information of actuator according to fluctuations of the velocity to minimize signal distortions. The UPF also resolves non-linearities of the actuator and non-normal distributions of noises. Effectiveness of the proposed algorithm has been verified through the real experiments and the results are demonstrated.

• Journal of Digital Convergence
• /
• v.12 no.11
• /
• pp.309-316
• /
• 2014

In this paper, we propose an efficient detph map creation method using Graph Cut and Discrete Wavelet Transform. First, we have segmented the original image by using Graph Cut to process with its each areas. After that, the information which describes segmented areas of original image have been created by proposed labeling method for segmented areas. And then, we have created four subbands which contain the original image's frequency information. Finally, the depth map have been created by frequency map which made with HH, HL subbands and depth information calculation along the each segmented areas. The proposed method can perform efficient depth map creation process because of dynamic allocation using depth information. We also have tested the proposed method using PSNR(Peak Signal to Noise Ratio) method to evaluate ours.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.1
• /
• pp.75-81
• /
• 2008

The induction motor is given a great deal of weight on the industry generally. Therefore, the fault of the induction motor may cause the fault to effect another parts or another faults in the whole system as well as in itself. These are accompany with a lose of the reliability in the industrial system. Accordingly to prevent these situation, the scholars have studies the fault diagnosis of the induction motor. In this paper, we proposed the diagnosis system of the induction motor. The method of diagnosis in proposed system is extracted the feature of the current signal by the wavelet transform. These extracted feature is used the automatic discrimination system by the neural network. We experiment the automatic discrimination system using the three faults imitation that often generated in the induction motor. The proposed system have achieved high reliable result with a simple devices about the three faults.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.23 no.3
• /
• pp.205-211
• /
• 2003

Acoustic emission (AE) technique has been applied to not only mechanical property testing but also on-line monitoring of the el)tire structure or a limit zone only. Although several AE devices have already been developed for the on-line monitoring, the price of these systems is very high and it is difficult for the field to apply yet. In this study, wc developed a specially designed PC-based source location system using the A/D board. The source location technique is very important to identify the source, such as crack, leak detection. However, since the AE waveforms obtained from transducers are very difficult to distinguish the defect signals, therefore, it is necessary to consider the signal analyses of the transient waveform. Wavelet Transform (WT) is a powerful tool for processing transient signals with temporally varying spectra that helps to resolve high and low frequency transients components effectively In this study, the analyses of the AE signals are presented by employing the WT analyses. AE results are compared the PC-based source location system using A/D board with the commercial AE system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.2C
• /
• pp.130-138
• /
• 2006

In this paper, a new stereo image watermarking scheme based-on adaptive disparity estimation algorithm is proposed. That is, a watermark image is embedded into the right image of a stereo image pair by using the DWT and disparity information is extracted from this watermarked right image and the left image. And then, both of this extracted disparity information and the left image are transmitted to the recipient through the communication channel. At the receiver, the watermarked right image is reconstructed from the received left image and disparity information through an adaptive matching algorithm. a watermark image is finally extracted from this reconstructed right image. From some experiments using CCETT's 'Manege' and 'Friends' images as a stereo image and English alphabet '3DRC' as a watermark image, it is found that the PSNRs of the watermarked image from the reconstructed right images through the adaptive matching algorithm & DWT is improved 2.03 dB, 3.03 dB and robusted against various attacks. These experimental results also suggest a possibility of practical implementation of an adaptive matching also-rithm-based stereo imagewatermarking scheme proposed in this paper.

• The KIPS Transactions:PartB
• /
• v.15B no.2
• /
• pp.87-94
• /
• 2008

In this paper, we propose a new vision-based fire detection method for a real-life application. Most previous vision-based methods using color information and temporal variation of pixel produce frequent false alarms because they used a lot of heuristic features. Furthermore there is also computation delay for accurate fire detection. To overcome these problems, we first detected candidated fire regions by using background modeling and color model of fire. Then we made probabilistic models of fire by using a fact that fire pixel values of consecutive frames are changed constantly and applied them to a Bayesian Network. In this paper we used two level Bayesian network, which contains the intermediate nodes and uses four skewnesses for evidence at each node. Skewness of R normalized with intensity and skewnesses of three high frequency components obtained through wavelet transform. The proposed system has been successfully applied to many fire detection tasks in real world environment and distinguishes fire from moving objects having fire color.