• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.731-737
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• 2014

This paper presents abnormal behavior detection in crowd within surveillance video. We have defined below two cases as a abnormal behavior; first as a sporadically spread phenomenon and second as a sudden running in same direction. In order to detect these two abnormal behaviors, we first extract the motion vector and propose a new descriptor which is combined MHOF(Multi-scale Histogram of Optical Flow) and DCHOF(Directional Change Histogram of Optical Flow). Also, binary classifier SVM(Support Vector Machine) is used for detection. The accuracy of the proposed algorithm is evaluated by both UMN and PETS 2009 dataset and comparisons with the state-of-the-art method validate the advantages of our algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.385-388
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• 2013

In this paper, we show the weakness of the image matching method by using MPEG-7 EHD(Edge Histogram Descriptor) and suggest how to improve this weakness by using image normalization. EHD algorithm is an image matching technique that collects edge's slope of distribution and same distribution. However, the EHD error rate is high because EHD is sensitive for changes of object distortion and rotation that will be matched. We improve matching performance by accurately extract edge information in image by using normalization. We compare and analyze the normalized EHD algorithm by using distortion and rotation and it shows robustness for changes of the size and rotation.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.111-119
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• 2006

Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with $\chi2$ histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

• Journal of Industrial Technology
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• v.18
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• pp.187-193
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• 1998

In this study, about the fatigue life of welded structure material under fluctuation loading, the prediction life which is produced by using the Histogram Recorder System was compared with the experimental life which is produced by the RMC model which is imported by conception of equivalent stress. In this result, this is represented few difference by comparing prediction life which is produced by damage analysis depended on Miner's rule, by using the Histogram Recorder System, with experimental life which is produced by the RMC load model which is imported by conception of equivalent of stress, therefore fatigue life is easily predicted by using Histogram Recorder System, and result of prediction has equivalent accuracy with other method which is more complex than the Histogram Recorder System. Besides the damage which is produced by stress which is high thirty percentage rank in the stress range of damage inducing, is nearly equal to the damage which is induced the rest of seventy percentage, there fore we can see that damage accumulation which is induced few time overload which is effected welded structure material is great.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1147-1154
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• 2011

Auto exposure (AE) in image signal processor (ISP) controls brightness of input image to the proper brightness when it is too dark or bright. But conventional AEs often fail to get proper brightness since AE controls only average brightness of image. Especially in applications that require object recognition, it cannot be solved the problem by AE of ISP. In this paper proposes Histogram Equalization (HE) processes that is the alternative of AE. It also proposes proper method to realize hardware and compensate HE problems conventional by using simple calculation.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.192-194
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• 2003

Since the details in quasi-homogeneous region will be destroyed from the conventional global image enhancement method such as histogram equalization. This defect is caused by the saturation of gray level in equalization process. So the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the region itself. To obtain the quasi- homogeneous regions, the original image must be segmented. Here we applied the watershed transform to the interesting image. Since the watershed transform is based on mathematical morphology, therefore, the regions touch can be effectively separated. Hence two adjacent regions which have the similar gray pixels will be split off. The process will be independently applied to three different spectral images. Then three different colors are assigned to each processed image in order to produce a color composite image. By the proposed algorithm, the result image shows the better perception on image details. Therefore, the high efficiency of image classification can be obtained by using this color image.

• KSCI Review
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• v.14 no.1
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• pp.255-264
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• 2006

Video viewers can not understand enough entire video contents because most video is long length data of large capacity. This paper propose efficient scene change detection and video abstracting using new shot clustering to solve this problem. Scene change detection is extracted by method that was merged color histogram with ${\chi}^2$ histogram. Clustering is performed by similarity measure using difference of local histogram and new shot merge algorithm. Furthermore, experimental result is represented by using Real TV broadcast program.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.16-18
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• 2012

Haze is an extreme reason of the reduction of contrast when capturing image in the outdoor. Recently, there are several single image dehazing techniques, but they are not robust in dynamic variations of natural environment caused by the thickness, coverage of haze and appearance of sunlight. In this paper, we propose an effective and robust method to enhance luminance for image dehazing depending on histogram analysis. Compare with conventional methods, our proposal have better performance in term of contrast, and computation time.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.153-156
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• 2002

The image labeling and classification is one of the important tasks for a content-based image retrieval and an image understanding. This paper propose a new technique to label and classify natural images with a color-spatial histogram and production rules. We show that our proposed method is very efficient for a natural image composed of a few regions.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.271-274
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• 2002

The YCbCr color is widely used for digital video. In this paper, six different histogram algorithms are defined; the corresponding test images are then produced; and these images are then evaluated by observers using psychophysical techniques such as pair comparison; and show observer's preference data based on the psychophysical experiment.