• ETRI Journal
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• v.41 no.5
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• pp.599-607
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• 2019

Although iris recognition verification is considered to be the safest method of biometric verification, studies have shown that iris features may be illegally used. To protect iris features and further improve the security of iris recognition and verification, this study applies the Gaussian and Laplacian mechanisms and to hide iris features by differentiating privacy. The efficiency of the algorithm and evaluation of the image quality by the image hashing algorithm are selected as indicators to evaluate these mechanisms. The experimental results indicate that the security of an iris image can be significantly improved using differential privacy protection.

• Journal of The Korean Association of Information Education
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• v.20 no.5
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• pp.527-534
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• 2016

This study is an analysis of Software image using the semantic differential scale with elementary students. We have selected the items in a total of 35 pairs of test about software-related image adjectives and are categorized into 7 main factors, and then analyzed the entire image with the students. The analysis of the differences between the software images of sex, the female students than male students were recognized the software is complex, slow and difficult and do not want to have. The analysis of the self-awareness on the software, the students who know that well recognized for the software select the positive term for the software. The inter-grade analysis are the older grade students were the answer to the objective features of the software like more difficult and complex.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1785-1801
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• 2017

In recent years, image encryption algorithms have been developed rapidly in order to ensure the security of image transmission. With the assistance of our previous work, this paper proposes a novel chaotic image encryption algorithm based on self-adaptive model and feedback mechanism to enhance the security and improve the efficiency. Different from other existing methods where the permutation is performed by the self-adaptive model, the initial values of iteration are generated in a novel way to make the distribution of initial values more uniform. Unlike the other schemes which is on the strength of the feedback mechanism in the stage of diffusion, the piecewise linear chaotic map is first introduced to produce the intermediate values for the sake of resisting the differential attack. The security and efficiency analysis has been performed. We measure our scheme through comprehensive simulations, considering key sensitivity, key space, encryption speed, and resistance to common attacks, especially differential attack.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.811-816
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• 2016

In light of recently developed 3D printers for rapid prototyping, there is increasing attention on the 3D scanner as a 3D data acquisition system for an existing object. This paper presents a prototypical 3D scanner based on a striped laser light image. In order to solve the problem of shadowy areas, the proposed 3D scanner has two cameras with one laser light source. By using a horizontal rotation table and a rotational arm rotating about the latitudinal axis, the scanner is able to scan in all directions. To remove an additional optical filter for laser light pixel extraction of an image, we have adopted a differential image method with laser light modulation. Experimental results show that the scanner's 3D data acquisition performance exhibited less than 0.2 mm of measurement error. Therefore, this scanner has proven that it is possible to reconstruct an object's 3D surface from point cloud data using a 3D scanner, enabling reproduction of the object using a commercially available 3D printer.

• Research in Community and Public Health Nursing
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• v.13 no.2
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• pp.376-386
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• 2002

Objectives: The purpose of this study was to investigate factors influencing the smoking behavior of adolescents, in order to provide basic data to develop a future nursing intervention program for smoking prevention. Methods: The study subjects were 162 adolescents attending high schools, who were living in K city. The instruments included the Self Esteem Scale translated by Jeon (1974), beliefs about the social rule scale developed by the Committee for Adolescence Guidance (1988), differential peer association developed by Krohn et. al. (1982), perceived behavioral control scale developed by Hanson (1997), intention of smoking scale developed by Newman et. al.(1982), and self-efficacy scale developed by Sherer et. al. (1982). The data were analyzed using descriptive statistics, Pearson correlation coefficient, and stepwise multiple regression. Results: 1. The smoking behaviors of the subjects were significantly correlated with beliefs about social rule, perceived behavioral control. differential peer association, intention of smoking, self efficacy, grade, father's level of education, monthly pocket money, time of onset for smoking, degree of alcoholic intake, and drug abuse. 2. The multiple regression analysis revealed the most powerful predictor for smoking behavior was time of onset for smoking. A combination of beliefs about social rule, perceived behavioral control, grade, differential peer association, and intention of smoking accounted for 54.0% of the variance for smoking behavior in adolescents. Conclusion: It is recommended that these influencing factors for smoking behavior be considered when developing future nursing intervention programs for the antismoking behaviors of adolescents.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.36-41
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• 2015

This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.

• Journal of KIISE:Software and Applications
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• v.37 no.6
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• pp.417-429
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• 2010

Reversible watermarking inserts watermark into digital media in such a way that visual transparency is preserved and then enables to restore the original media from the marked one without any loss of media quality. This watermarking can be applied to quality-sensitive imaging such as medical imaging, military imaging, remote-sensing imaging, and precious artwork, where the original media should be preserved during image processing and analysis. In this paper, a reversible image watermarking technique that embeds message bits by modifying the differential histogram of adjacent pixels is presented. In order to satisfy both high embedding capacity and visual quality, the proposed technique exploits the fact that adjacent pixels in the image have highly spatial correlation. Also, we prevent overflow/underflow problem and salt-and-pepper artifacts by employing a predicted error compensation scheme. Through experiments using various test images, we prove that the presented technique provides perfect reversibility and high embedding capacity, while maintaining the induced-distortion low.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1185-1198
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• 1992

In this paper, the differential weighted algorithm proposed in order to improve th noise smoothing characteristics of conventional Median filter and FIR-Median Hybrid filter. Performance of some image restoration filter(median filter, FIR-Median Hybird filter, FIR-Median Hybrid filter to proposed differential weighted algorithm) are compared and evaluated on the noise smoothing characteristics and sharp edge conservation characteristics. Test and Real images used in this paper are Lenna and Urological images corrupted by impulse, gaussian, exponential and laplacian noise. Experimental results show that the FIR-Median Hybrid filter applied to the differential weighted algorithm are comparatively superior to others. But the filter orders have increased, the more time consumed to image processing. Hence if the adequate filtering by the type of image is selected. now after a great support will be take consideration into the various parts of application by computer science and of medical image processing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.643-650
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• 2014

A hardware implementation of phase calculator for extracting 3D depth image from TOF(Time-Of-Flight) sensor is described. The designed phase calculator adopts redundant binary number systems and a pipelined architecture to improve throughput and speed. It performs arctangent operation using vectoring mode of DCORDIC(Differential COordinate Rotation DIgital Computer) algorithm. Fixed-point MATLAB simulations are carried out to determine the optimal bit-widths and number of iteration. The phase calculator has ben verified by FPGA-in-the-loop verification using MATLAB/Simulink. A test chip has been fabricated using a TSMC $0.18-{\mu}m$ CMOS process, and test results show that the chip functions correctly. It has 82,000 gates and the estimated throughput is 400 MS/s at 400Mhz@1.8V.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1549-1557
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• 1999

In this paper, we propose a face recognition algorithm based on the differential image method-DCT This algorithm uses neural networks which is flexible for noise. Using the same condition (same luminous intensity and same distance from the fixed CCD camera to human face), we have captured two images. One doesn't contain human face. The other contains human face. Differential image method is used to separate the second image into face region and background region. After that, we have extracted square area from the face region, which is based on the edge distribution. This square region is used as the characteristics region of human face. It contains the eye bows, the eyes, the nose, and the mouth. After executing DCT for this square region, we have extracted the feature vectors. The feature vectors were normalized and used as the input vectors of the neural network. Simulation results show 100% recognition rate when face images were learned and 92.25% recognition rate when face images weren't learned for 30 persons.