• Current Optics and Photonics
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• v.7 no.4
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• pp.362-377
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• 2023

Optical information processing technology is characterized by high speed and parallelism, and the light features short wavelength and large information capacity; At the same time, it has various attributes including amplitude, phase, wavelength and polarization, and is a carrier of multi-dimensional information. Therefore, optical encryption is of great significance in the field of information security transmission, and is widely used in the field of image encryption. For multi-image encryption, this paper proposes a multi-image encryption algorithm based on a modified Gerchberg-Saxton algorithm (MGSA) in the Fresnel-transform domain and computational ghost imaging. First, MGSA is used to realize "one code, one key"; Second, phase function superposition and normalization are used to reduce the amount of ciphertext transmission; Finally, computational ghost imaging is used to improve the security of the whole encryption system. This method can encrypt multiple images simultaneously with high efficiency, simple calculation, safety and reliability, and less data transmission. The encryption effect of the method is evaluated by using correlation coefficient and structural similarity, and the effectiveness and security of the method are verified by simulation experiments.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.6
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• pp.1016-1026
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• 1996

The purpose of this study was to extract protypes from features and concrete images of Lotus and Crane patterns. A qualitative and a quantitative methods were used. Qualitative informations were obtained from depth Interviews for pattern selection and feature extraction, and quantitative informations from a quail-experiment for pattern caregorization. The subjects were 20 female design students and non-design, students in Teajon. The results were summerized into a similarity metrix which was interpreted by the cluster analysis and the multi-dimensional scling(MDS). The patterns for the study were grouped into 8 clusters. Four dimensions were chosen for the MDS. The location of each pattern was visualized in a 2-dimesional spaces and the location of each cluster in a 3-dimensional spaces. The first dimension, "Lotus" vs "Crane" refired to pattern types, and the second dimension, "realistic" vs "transformable", the transformability. The third dimension, "simple" vs "complex", refired to the degree of simplification, and the forth dimension, "continuous" vs "discontinuous", continuity. The results of the Quantitative analysis could be summerized into 3-level prototype hiararchy In the first level, the patterns were devided clearly into two groups. Lotus and Crane by pattern types. In the second levelk, each group was devided into twosubgroups by continuity. In the third, each subgroup was divided into four subgroups by transformability and the degree of simplification. Four protypes, the final targets of the present study, were extracted from the third level. The are Stylized, Realistic, Decorative, Abstract types.d from the third level. The are Stylized, Realistic, Decorative, Abstract types.

• Environmental Engineering Research
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• v.20 no.1
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• pp.1-18
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• 2015

The biosorption process has been established as characteristics of dead biomasses of both cellulosic and microbial origin to bind metal ion pollutants from aqueous suspension. The high effectiveness of this process even at low metal concentration, similarity to ion exchange treatment process, but cheaper and greener alternative to conventional techniques have resulted in a mature biosorption technology. Yet its adoption to large scale industrial wastewaters treatment has still been a distant reality. The purpose of this review is to make in-depth analyses of the various aspects of the biosorption technology, staring from the various biosorbents used till date and the various factors affecting the process. The design of better biosorbents for improving their physico-chemical features as well as enhancing their biosorption characteristics has been discussed. Better economic value of the biosorption technology is related to the repeated reuse of the biosorbent with minimum loss of efficiency. In this context desorption of the metal pollutants as well as regeneration of the biosorbent has been discussed in detail. Various inhibitions including the multi mechanistic role of the biosorption technology has been identified which have played a contributory role to its non-commercialization.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.10-18
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• 2010

Due to a large number of classes in Hangul character recognition, it is usual to use the six-type preclassification stage. After the preclassification, the first consonent, vowel, and last consonent can be classified separately. Though each of three components has a few of classes, classification errors occurs often due to shape similarity such as 'ㅔ' and 'ㅖ'. So this paper proposes a hierarchical recognition method which adopts multi-stage tree structures for each of 6-types. In addition, to reduce the interference among three components, the method uses the recognition results of first consonents and vowel as features of vowel classifier. The recognition accuracy for the test set of PHD08 database was 98.96%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.15-29
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• 2024

A fetoscope is an optical endoscope, which is often applied in fetoscopic laser photocoagulation to treat twin-to-twin transfusion syndrome. In an operation, the clinician needs to observe the abnormal placental vessels through the endoscope, so as to guide the operation. However, low-quality imaging and narrow field of view of the fetoscope increase the difficulty of the operation. Introducing an accurate placental vessel segmentation of fetoscopic images can assist the fetoscopic laser photocoagulation and help identify the abnormal vessels. This study proposes a method to solve the above problems. A novel encoder-decoder network with a dual-path structure is proposed to segment the placental vessels in fetoscopic images. In particular, we introduce a channel attention mechanism and a continuous convolution structure to obtain multi-scale features with their weights. Moreover, a switching connection is inserted between the corresponding blocks of the two paths to strengthen their relationship. According to the results of a set of blood vessel segmentation experiments conducted on a public fetoscopic image dataset, our method has achieved higher scores than the current mainstream segmentation methods, raising the dice similarity coefficient, intersection over union, and pixel accuracy by 5.80%, 8.39% and 0.62%, respectively.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.57-63
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• 2009

The rapid growth of computer-based image database, necessity of a system that can manage an image information is increasing. This paper presents a region-based image retrieval method using the combination of color(autocorrelogram), texture(CWT moments) and shape(Hu invariant moments) features. As a color feature, a color autocorrelogram is chosen by extracting from the hue and saturation components of a color image(HSV). As a texture, shape and position feature are extracted from the value component. For efficient similarity confutation, the extracted features(color autocorrelogram, Hu invariant moments, and CWT moments) are combined and then precision and recall are measured. Experiment results for Corel and VisTex DBs show that the proposed image retrieval algorithm has 94.8% Precision, 90.7% recall and can successfully apply to image retrieval system.

• Journal of The Korean Astronomical Society
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• v.46 no.5
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• pp.191-200
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• 2013

Full-disk solar images are provided by many solar telescopes around the world. However, the observed images show Non-Radial Variation (NRV) over the disk. In this paper, we propose algorithms for detecting distortions and restoring these images. For detecting NRV, the cross-correlation coefficients matrix of radial profiles is calculated and the minimum value in the matrix is defined as the Index of Non-radial Variation (INV). This index has been utilized to evaluate the H images of GONG, and systemic variations of different instruments are obtained. For obtaining the NRV's image, a Multi-level Morphological Filter (MMF) is designed to eliminate structures produced by solar activities over the solar surface. Comparing with the median filter, the proposed filter is a better choice. The experimental results show that the effect of our automatic detection and restoration methods is significant for getting a flat and high contrast full-disk image. For investigating the effect of our method on solar features, structural similarity (SSIM) index is utilized. The high SSIM indices (close to 1) of solar features show that the details of the structures remain after NRV restoring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.543-548
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• 2021

The higher the resolution of the image, the higher the satisfaction of the viewers of the image, and the super-resolution imaging has a considerable increase in research value among the fields of computer vision and image processing. In this study, the main features of low-resolution image LR are extracted mainly using deep learning super-resolution models. It learns and reconstructs the extracted features, and focuses on reconstruction-based algorithms that generate high-resolution image HR. In this paper, we investigate SRCNN and VDSR in a super-resolution algorithm model based on reconstruction. The structure and algorithm process of the SRCNN and VDSR model are briefly introduced, and the multi-channel and special form are also examined in the improved performance evaluation function, and understand the performance of each algorithm through experiments. In the experiment, an experiment was performed to compare the results of the SRCNN and VDSR models with the peak signal-to-noise ratio and image structure similarity, so that the results can be easily judged.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.683-690
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• 2004

Garment modeling and simulation is now one of the important elements in broad range of digital contents. Though there have been recent products on garment simulation, general users do not know well enough how to design a virtual costume that meets some requirements about its specific clothing pattern. In particular, Hanbok - the Korean traditional costume - has many different characteristics against western ones in the aspect of its pattern design and of draping. This paper presents a knowledge-driven approach for virtual Hanbok modeling without knowing how to make real Hanbok. First, parameterized knowledge for several fabric types art solicited using visual similarity assessment from simulated and real cloth. Secondly, based on the analysis of designer's knowledge, we defined multi-level adjustment processes of Hanbok measurements with regard to body shape features for different virtual actors. An experimental system is developed as the form of a Maya plug-in and the result shows the applicability of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.431-437
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• 2004

This paper propose a facial recognition method based on an ubiquitous computing that is one of next generation intelligence technology fields. The facial images are acquired by a mobile device so-called cellular phone camera. We consider a mobile security using facial feature extraction and recognition process. Facial recognition is performed by the PCA and fuzzy LDA algorithm. Applying the discrete wavelet based on multi-resolution analysis, we compress the image data for mobile system environment. Euclidean metric is applied to measure the similarity among acquired features and then obtain the recognition rate. Finally we use the mobile equipment to show the efficiency of method. From various experiments, we find that our proposed method shows better results, even though the resolution of mobile camera is lower than conventional camera.