• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2862-2878
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• 2020

Data Security is the most challenging area in Internet communication, where most of the secret sharing schemes are proposed for binary images. But still it lacks in providing security for data communication, especially in image transmission. Traditional visual cryptography scheme generate meaningless diwies and the reconstruction phase leads to quality degradation over the secret image. In this work, an intelligent two dimensional secret share construction scheme is proposed. A secret image is expanded into n diwies with the choice of scheme selection. By Stacking all the qualified diwies to revert the secret image without content loss and less than s^* - 1 shares could not reveal any information about the secret image. The experimental results emphasize that the proposed secret share scheme is highly secured for image transmission.

• Journal of Korea Multimedia Society
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• v.15 no.11
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• pp.1369-1376
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• 2012

In this paper, we propose 2D industrial image registration method for the detection of defects. Proposed method performs preprocessing to smooth the original image with the preservation of the edge for the robust registration against general noise. Then, x-direction gradient magnitude image and corresponding binary image are generated. Density analysis around neighborhood regions per pixel are performed to generate feature image for preventing mis-registration due to moire-like patterns, which frequently happen in industrial images. Finally, 2D image registration based on phase correlation between feature images is performed to calculate translational parameters to align two images rapidly and optimally. Experimental results showed that the registration accuracy of proposed method for the real industrial images was 100% and our method was about twenty times faster than the previous method. Our fast and accurate method could be used for the real industrial applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.935-943
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• 1993

In this paper, robust recognition system for tilted facial image was developed. At first, standard facial image and lilted facial image are captured by CCTV camera and then transformed into binary image. The binary image is processed in order to obtain contour image by Laplacian edge operator. We trace and delete outermost edge line and use inner contour lines. We label four inner contour lines in order among the inner lines, and then we extract left and right eye with known distance relationship and with two eyes coordinates, and calculate slope information. At last, we rotate the tilted image in accordance with slope information and then calculate the ten distance features between element and element. In order to make the system invariant to image scale, we normalize these features with distance between left and righ eye. Experimental results show 88% recognition rate for twenty five face images when tilted degree is considered and 60% recognition rate when tilted degree is not considered.

• Journal of ILASS-Korea
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• v.21 no.2
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• pp.88-94
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• 2016

In this study digital holographic microscopy system for measurements of 3-D velocities of particles in MR fluid is developed. Holograms are recorded using either a CCD camera with a double pulse laser or a high-speed camera with a continuous laser. To process recorded holograms, the correlation coefficient method is used for focal plane determination of particles. To remove noise and improve the quality of holograms and reconstructed images, a Wiener filter is adopted. The two-threshold and image segmentation methods are used for binary image transformation. For particle pairing, the match probability method is adopted. The developed system will be applied to measurements of the characteristics of unsteady 3-D particle velocities in MR fluids through the next stage of this study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.789-796
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• 2013

It is known that the detection of hopping signals without any information about hopping duration and hopping frequency is rather difficult. This paper considers the blind detection of hopping signal's information such as hopping duration and hopping frequency from the sampled wideband signals. In order to find hopping information from the wideband signals, multiple narrow-band filters are required in general, which leads to huge implementation complexity. Instead, this paper employs the polyphase DFT(discrete Fourier transform) filterbank to reduce the implementation complexity. This paper propose hopping signal detection algorithm from the polyphase DFT filterbank output. Specifically, based on the binary image processing, the proposed algorithm is developed to decrease the memory size and H/W complexity. The performance of the proposed algorithm is evaluated through the computer simulation and FPGA (field programmable gate array) implementation.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.671-680
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• 2015

The Joint Bayesian[1] method was published in 2012. Since then, it has been used for binary classification in almost all state-of-the-art face recognition methods. However, no improved methods have been published so far except 2D-JB[2]. In this paper we propose an improved version of the JB method that considers the features of both the given face image and its mirror image. In pattern classification, it is very likely to make a mistake when the value of the decision function is close to the decision boundary or the threshold. By making the value of the decision function far from the decision boundary, the proposed method reduces the errors. The experimental results show that the proposed method outperforms the JB and 2D-JB methods by more than 1% in the challenging LFW DB. Many state-of-the-art methods required tons of training data to improve 1% in the LFW DB, but the proposed method can make it in an easy way.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2615-2628
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• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2251-2259
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• 2009

We propose an algorithm and system which generates 3D stereo image by composition of 2D image from 4 multiple clusters which 1 cluster was composed of 4 multiple cameras based on network. Proposed Schemes have a network-based client-server architecture for load balancing of system caused to process a large amounts of data with real-time as well as multiple cluster environments. In addition, we make use of JPEG compression and RAM disk method for better performance. Our scheme first converts input images from 4 channel, 16 cameras to binary image. And then we generate 3D stereo images after applying edge detection algorithm such as Sobel algorithm and Prewiit algorithm used to get disparities from images of 16 multiple cameras. With respect of performance results, the proposed scheme takes about 0.05 sec. to transfer image from client to server as well as 0.84 to generate 3D stereo images after composing 2D images from 16 multiple cameras. We finally confirm that our scheme is efficient to generate 3D stereo images in multiple view and multiple clusters environments with real-time.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.2
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• pp.101-109
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• 1998

In this paper, we implemented holographic optical memory systm which can store and reconstruct many images using new input and angular multiplexing method. In the new input method, phase infomation of input image is inputed in the recording material instead of brightness information. To do so, we represented the images, which captured with CCD camera or displayed on the computer monitor, on the liquid crystal television(LCTV) which removed polarizer/analyzer. Therefore, we can generate uniform input beam intensity regardless of the total brightness of input image, and apply the scheduled recording method. Also we can increase the intensity of input beam so reduce the recording time of input image. And reconstructedimage is acquired by transforming phase information into brightness information of image with analyzer. The incident angle of reference beam is acquired by Fourier transform of the binary phase hologram(BPH) which designed with SA algorithm on the LCTV. The proposed optical memory system is stable because the incident angle of the reference beam is controlled easy and electronically. We demonstreated optical experiment which store and reconstruct various type images in BaTiO$_{3}$ using proposed holographic memory system.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.575-580
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• 2010

Eye gaze as a form of input was primarily developed for users who are unable to use usual interaction devices such as keyboard and the mouse; however, with the increasing accuracy in eye gaze detection with decreasing cost of development, it tends to be a practical interaction method for able-bodied users in soon future as well. This paper explores a low-cost, robust, rotation and illumination independent eye gaze system for gaze enhanced user interfaces. We introduce two brand-new algorithms for fast and sub-pixel precise pupil center detection and 2D Eye Gaze estimation by means of deformable template matching methodology. In this paper, we propose a new algorithm based on the deformable angular integral search algorithm based on minimum intensity value to localize eyeball (iris outer boundary) in gray scale eye region images. Basically, it finds the center of the pupil in order to use it in our second proposed algorithm which is about 2D eye gaze tracking. First, we detect the eye regions by means of Intel OpenCV AdaBoost Haar cascade classifiers and assign the approximate size of eyeball depending on the eye region size. Secondly, using DAISMI (Deformable Angular Integral Search by Minimum Intensity) algorithm, pupil center is detected. Then, by using the percentage of black pixels over eyeball circle area, we convert the image into binary (Black and white color) for being used in the next part: DTBGE (Deformable Template based 2D Gaze Estimation) algorithm. Finally, using DTBGE algorithm, initial pupil center coordinates are assigned and DTBGE creates new pupil center coordinates and estimates the final gaze directions and eyeball size. We have performed extensive experiments and achieved very encouraging results. Finally, we discuss the effectiveness of the proposed method through several experimental results.