• Journal of Digital Contents Society
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• v.10 no.3
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• pp.423-431
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• 2009

There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.61-74
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• 2012

In this paper, we propose a illumination-robust face recognition system using MCS-LBP and 2D-PCA algorithm. A binary pattern transform which has been used in the field of the face recognition and facial expression, has a characteristic of robust to illumination. Thus, this paper propose MCS-LBP which is more robust to illumination than previous LBP, and face recognition system fusing 2D-PCA algorithm. The performance evaluation of proposed system was performed by using various binary pattern images and well-known face recognition features such as PCA, LDA, 2D-PCA and ULBP histogram of gabor images. In the process of performance evaluation, we used a YaleB face database, an extended YaleB face database, and a CMU-PIE face database that are constructed under varying lighting condition, and the proposed system which consists of MCS-LBP image and 2D-PCA feature show the best recognition accuracy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.30-36
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• 2008

The multimedia that is characterized by multi-media, multi-features, multi-representations, huge volume, and varieties, is rapidly spreading out due to the increasing of application domains. Thus, it is urgently needed to develop a multimedia information system that can retrieve the needed information rapidly and accurately from the huge amount of multimedia data. For the content-based retrieval of moving picture, picture information is generally used. It is generally used when video is segmented. Through that, it can be a structural video browsing. The tasking that divides video to shot is called video segmentation, and detecting the cut for video segmentation is called cut detection. The goal of this paper is to divide moving picture using HMMD(Hue-Mar-Min-Diff) color model and edge histogram descriptor among the MPEG-7 visual descriptors. HMMD color model is more familiar to human's perception than the other color spaces. Finally, the proposed retrieval system is implemented as hardware.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.1987-1996
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• 2009

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.205-208
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• 2013

Generally, binary pattern transforms have been used in the field of the face recognition and facial expression, since they are robust to illumination. Thus, this paper proposes an illumination-robust face recognition system combining an MLDP, which improves the texture component of the LDP, and a 2D-PCA algorithm. Unlike that binary pattern transforms such as LBP and LDP were used to extract histogram features, the proposed method directly uses the MLDP image for feature extraction by 2D-PCA. The performance evaluation of proposed method was carried out using various algorithms such as PCA, 2D-PCA and Gabor wavelets-based LBP on Yale B and CMU-PIE databases which were constructed under varying lighting condition. From the experimental results, we confirmed that the proposed method showed the best recognition accuracy.

• The Journal of the Petrological Society of Korea
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• v.18 no.4
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• pp.315-336
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• 2009

We have studied the orientational characteristics of microcrack frequency, it's length and density in Tertiary crystalline tuff from the northeastern part of the Gyeongsang Basin. 134 sets of microcracks on horizontal surfaces of 3 rock samples from Heunghae-eup were distinguished by enlarged photomicrographs of the thin sections. The variability in patterns among microcrack length-frequency histograms for three rock samples from different altitudes were derived. The pattern of histograms changes progressively from negative exponential form to log-normal form in proportion to altitude. The distribution pattern for rock sample no.1 from lower altitude shows the broad length distribution characterized by higher mean and median, and higher standard deviation. Meanwhile, this distribution pattern corresponds with characteristics of joint length distribution in sedimentary rocks of the lower part of the Gyeongsang Supergroup. The occurrence frequency of shorter microcracks increases toward both NW and NE directions from the $N0{\sim}10^{\circ}W$, with the dominant direction of $N80{\sim}90^{\circ}W$ and $N80{\sim}90^{\circ}E$, respectively. This distribution pattern represents the relative differences in formation timing among microcrack sets and the result of the new initiation of shorter microcracks. Meanwhile, the longest microcracks within $N60{\sim}70^{\circ}W$($L_{max}$:1.18 mm) and $N0{\sim}10^{\circ}W$($L_{max}$:0.80 mm) directions are seen, but this kind of microcracks are very limited in number. Whole domain of the directional angle($\theta$)-frequency(N), length(L) and density($\rho$) chart can be divided into five sections in terms of phases of the distribution of related curves. From the distribution chart, density curve shows five distinct peaks in the WNW-ESE($N70{\sim}80^{\circ}W$), NS~NNE-SSW($N0{\sim}10^{\circ}W$, $N10{\sim}20^{\circ}E$), ENE-WSW($N50{\sim}60^{\circ}E$), and nearly EW($N80{\sim}90^{\circ}E$) directions, respectively. Especially, main directions of faults correspond with the directional angle showing high density. Consequently, these distribution patterns of density curve reflect the representative maximum principal stress orientations suggested in previous studies.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.39-47
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• 2019

In this paper, we proposed extracting modified Histogram of Oriented Gradients (HOG) features using background removal when tracking pedestrians in real time. HOG feature extraction has a problem of slow processing speed due to large computation amount. Background removal has been studied to improve computation reductions and tracking rate. Area removal was carried out using S and V channels in HSV color space to reduce feature extraction in unnecessary areas. The average S and V channels of the video were removed and the input video was totally dark, so that the object tracking may fail. Histogram equalization was performed to prevent this case. HOG features extracted from the removed region are reduced, and processing speed and tracking rates were improved by extracting clear HOG features. In this experiment, we experimented with videos with a large number of pedestrians or one pedestrian, complicated videos with backgrounds, and videos with severe tremors. Compared with the existing HOG-SVM method, the proposed method improved the processing speed by 41.84% and the error rate was reduced by 52.29%.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.938-943
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• 2003

In this paper, we Propose a method using the Tikhonov-Miller process to improve the robustness of watermarking under various attacks. A visually recognizable pattern watermark is embedded in the LH2, HL2 and HH2 subband of wavelet transformed domain using threshold and besides watermark is embeded by utilizing HVS(Human Visual System) feature. The pattern watermark was interlaced after random Permutation for a security and an extraction rate. To demonstrate the improvement of robustness and similarity of the proposed method, we applied some basic algorithm of image processing such as scaling, filtering, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method was able to embed robust watermark invisibility and extract with an excellent normalized correlation of watermark under various attacks.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.8-15
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• 2007

Recently, it is important to process multimedia data efficiently. Especially, in case of retrieval of multimedia information, technique of user interface and retrieval technique are necessary. This paper proposes a new technique which detects cuts effectively in compressed image information by MPEG. A cut is a turning point of scenes. The cut-detection is the basic work and the first-step for video indexing and retrieval. Existing methods have a weak point that they detect wrong cuts according to change of a screen such as fast motion of an object, movement of a camera and a flash. Because they compare between previous frame and present frame. The proposed technique detects shots at first using DC(Direct Current) coefficient of DCT(Discrete Cosine Transform). The database is composed of these detected shots. Features are extracted by HMMD color model and edge histogram descriptor(EHD) among the MPEG-7 visual descriptors. And detections are performed in sequence by the proposed matching technique. Through this experiments, an improved video segmentation system is implemented that it performs more quickly and precisely than existing techniques have.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.171-180
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• 2013

Data security is always an important issue. In particular, the current emerging cloud computing system inevitably raises the issue of data security. However, data security is no longer safe with a simple way, but requires rather advanced method to secure the data. In this paper, instead of exploiting the existing text-based cryptography approach an image-based access control of data content is studied to present a higher level of data security. Color key chain is generated both using histogram value of the original image, and the location information and featured color information extracted by geometric transformation to form the security key to access secure data content. Finally, the paper addresses design interface and implementation for data content access control for evaluation of the proposed scheme.