• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.515-524
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• 2013

In this paper, we propose a novel face authentication method based on LBP matching of individual major blocks in mobile environment. In order to construct individual major blocks from photos, we find the blocks that have the highest similarity and use different numbers of blocks depending on the probability distribution by applying threshold. And, we use multi-radius LBP histograms in the determination of individual major blocks to improve performance of generic LBP histogram based approach. By using the multi-radius LBP histograms in face authentication, we can successfully reduce the false acceptance rate compare to the previous methods. Also, we can see that the proposed method shows low error rate about 7.72% compare to the pervious method in spite of use small number of blocks about 44.59% only.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1302-1309
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• 2008

Traditional clustering methods, like k-means or fuzzy clustering, are prototype-based methods which are applicable only to convex clusters. On the other hand, spectral clustering tries to find clusters only using local similarity information. Its ability to handle concave clusters has gained the popularity recent years together with support vector machine (SVM) which is a kernel-based classification method. However, as is in SVM, the kernel width plays an important role and has a great impact on the result. Several methods are proposed to decide it automatically, it is still determined based on heuristics. In this paper, we proposed an adaptive method deciding the kernel width based on distance histogram. The proposed method is motivated by the fact that the affinity matrix should be formed into a block diagonal matrix to generate the best result. We use the tradition Euclidean distance together with the random walk distance, which make it possible to form a more apparent block diagonal affinity matrix. Experimental results show that the proposed method generates more clear block structured affinity matrix than the existing one does.

• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.185-195
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• 2013

In this paper, we propose a video summarization technique on a smartphone, based on spatiotemporal saliency. The proposed technique detects scene changes by computing the difference of the color histogram, which is robust to camera and object motion. Then the similarity between adjacent frames, face region, and frame saliency are computed to analyze the spatiotemporal saliency in a video clip. Over-segmented hierarchical tree is created using scene changes and is updated iteratively using mergence and maintenance energies computed during the analysis procedure. In the updated hierarchical tree, segmented frames are extracted by applying a greedy algorithm on the node with high saliency when it satisfies the reduction ratio and the minimum interval requested by the user. Experimental result shows that the proposed method summaries a 2 minute-length video in about 10 seconds on a commercial smartphone. The summarization quality is superior to the commercial video editing software, Muvee.

• Journal of KIISE
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• v.44 no.7
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• pp.692-702
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• 2017

Face detection using the LBP based feature descriptor has issues in that it can not represent spatial information between facial shape and facial components such as eyes, nose and mouth. To address these issues, in previous research, a facial image was divided into a number of square sub-regions. However, since the sub-regions are divided into different numbers and sizes, the division criteria of the sub-region suitable for the database used in the experiment is ambiguous, the dimension of the LBP histogram increases in proportion to the number of sub-regions and as the number of sub-regions increases, the sensitivity to facial orientation rotation increases significantly. In this paper, we present a novel facial region segmentation method that can solve in-plane rotation issues associated with LBP based feature descriptors and the number of dimensions of feature descriptors. As a result, the proposed method showed detection accuracy of 99.0278% from a single facial image rotated in orientation.

• The Journal of the Korea Contents Association
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• v.2 no.3
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• pp.1-15
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• 2002

A noel automated brain region extraction method in single channel MR images for visualization and analysis of a human brain is presented. The method generates a volume of brain masks by automatic thresholding using a dual curve fitting technique and by 3D morphological operations. The dual curve fitting can reduce an error in clue fitting to the histogram of MR images. The 3D morphological operations, including erosion, labeling of connected-components, max-feature operation, and dilation, are applied to the cubic volume of masks reconstructed from the thresholded Drain masks. This method can automatically extract a brain region in any displayed type of sequences, including extreme slices, of SPGR, T1-, T2-, and PD-weighted MR image data sets which are not required to contain the entire brain. In the experiments, the algorithm was applied to 20 sets of MR images and showed over 0.97 of similarity index in comparison with manual drawing.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.6
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• pp.705-716
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• 2002

This paper proposes a method which visualizes MRI head data in 3 dimensions with direct volume rendering. Though surface rendering is usually used for MRI data visualization, it has some limits of displaying little speckles because it loses the information of the speckles in the surfaces while acquiring the information. Direct volume rendering has ability of displaying little speckles, but it doesn't treat MRI data because of the data features of MRI. In this paper, we try to visualize MRI head data in 3 dimensions as follows. First, we separate the brain region from the head region of MRI head data, next increase the pixel level of the brain region, then combine the brain region with the increased pixel level and the head region without brain region, last visualizes the combined MRI head data with direct volume rendering. We segment the brain region from head region based on histogram threshold, morphology operations and snakes algorithm. The proposed segmentation method shows 91~95% similarity with a hand segmentation. The method rather clearly visualizes the organs of the head in 3 dimensions.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.236-247
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• 2010

Recently, mean shift tracking algorithms have been proposed which use the information of color histogram together with some spatial information provided by the kernel. In spite of their fast speed, the algorithms are suffer from an inherent instability problem which is due to the use of an isotropic kernel for spatiality and the use of the Bhattacharyya coefficient as a similarity function. In this paper, we analyze how the kernel and the Bhattacharyya coefficient can arouse the instability problem. Based on the analysis, we propose a novel tracking scheme that uses a new representation of the location of the target which is constrained by the color, the area, and the spatiality information of the target in a more stable way than the mean shift algorithm. With this representation, the target localization in the next frame can be achieved by one step computation, which makes the tracking stable, even in difficult situations such as low-rate-frame environment, and partial occlusion.

• The KIPS Transactions:PartB
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• v.11B no.2
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• pp.149-158
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• 2004

This study proposes a method for segmentation and recognition of traffic signs using shape information and edge image in real image. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic signs based on their symmetries on X- and Y-axes. Histogram equalization is performed for unsegmented candidate regions caused by low contrast in the image. In the recognition stage, it utilizes shape information including projection profiles on X- and Y-axes, moment, and the number of crossings and distance which concentric circular patterns and 8-directional rays from region center intersects with edges of traffic signs. It finally performs recognition by measuring similarity with the templates in the database. It will be shown from several experimental results that the system is robust to environmental factors, such as light and weather condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1006-1014
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• 2020

Consumer expectations for drama VFX increased as the influx of overseas dramas increased due to the growth of OTT service, but the current production time of the drama production system has a negative effect on the quality and completion of work. This paper proposes a background rendering using a game engine and a subject rendering using background HDRI as environmental lighting. The proposed workflow is expected to reduce the production time of VFX and improve the quality of VFX. The proposed workflow was verified in 3 steps. Comparing game engine and rendering software according to the same lighting environment and camera distance, comparing rendering with existing rendering method and background HDRI generation, and validating the proposed workflow. For verification, quantitative evaluation was performed using Structual similarity index and histogram. This study is expected to be one of the options to improve the quality of VFX and improve the risk.

• The Journal of Korean Society for Radiation Therapy
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• v.19 no.2
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• pp.113-122
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• 2007

Purpose: We proposed the method using dose-volume Histogram index to compare prospective plan trials in tomotherapy planning optimization. Materials and Methods: For 3 patients in cranial region, thorax and abdominal region, we acquired computed tomography images with PQ 5000 in each case. Then we delineated target structure and normal organ contour with pinnacle Ver 7.6c, after transferred each data to tomotherapy planning system (hi-art system Ver 2.0), we optimized 3 plan trials in each case that used differ from beam width, pitch, importance. We analyzed 3 plan trials in each region with isodose distribution, dose-volume histogram and dose statistics. Also we verified 3 plan trials with specialized DVH-indexes that is dose homogeneity index in target organ, conformity index around target structure and dose gradient index in non-target structures. Results: We compared with the similarity of results that the one is decide the best plan trial using isodose distribution, dose volume histogram and dose statistics, and the another is using DVH-indexes. They all decided the same plan trial to better result in each case. Conclusion: In some of case, it was appeared a little difference of results that used to DVH-index for comparison of plan trial in tomotherapy by special goal in it. But because DVH-index represented both dose distribution in target structure and high dose risk about normal tissue, it will be reasonable method for comparison of many plan trials before the tomotherapy treatments.