• Journal of Information Technology Applications and Management
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• v.9 no.3
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• pp.1-12
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• 2002

Due to the fast development in computer and communication technologies, a video is now being more widely used than ever in many areas. The current information analyzing systems are originally built to process text-based data. Thus, it has little bits problems when it needs to correctly represent the ambiguity of a video, when it has to process a large amount of comments, or when it lacks the objectivity that the jobs require. We would like to purpose an algorithm that is capable of analyze a large amount of video efficiently. In a video, divided areas use a region growing and region merging techniques. To sample the color, we translate the color from RGB to HSI and use the information that matches with the representative colors. To sample the shape information, we use improved moment invariants(IMI) so that we can solve many problems of histogram intersection caused by current IMI and Jain. Sampled information on characteristics of the streaming media will be used to find similar frames.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.108-117
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• 2022

The recent development of information and communication technology has a great impact on the audio/video industry. In particular, IP-based AoIP transmission technology and AVB technology are making changes in the audio/video market. Video signal transmission technology has been introduced to the market through a network, but it has not replaced the video switcher function. Video signals in the conference room or classroom are still controlled by the switching device. In order to switch input/output video devices, a cable that is not limited by distance must be connected to the switcher. In addition, the control of the switching device must be performed by a person who has received professional training. In this paper, it is a technology that can be operated even by non-experts by replacing complex video cables (RGB, DVI, HDMI, DP) with LAN cables and enabling IP-based video switching and transmission (Video Mirroring over IP: VMoIP) to replace video switcher equipment. We are going to do this study, I/O videos were controlled in the form of matrix and high-definition videos were transmitted without distortion, and VMoIP is expected to become the standard for video switching systems in the future.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.4
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• pp.281-290
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• 2015

Human action recognition from a video scene has remained a challenging problem in the area of computer vision and pattern recognition. The development of the low-cost RGB depth camera (RGB-D) allows new opportunities to solve the problem of human action recognition. In this paper, we present a comprehensive review of recent approaches to human action recognition based on depth maps, skeleton joints, and other hybrid approaches. In particular, we focus on the advantages and limitations of the existing approaches and on future directions.

• Journal of the Korean Society for Nondestructive Testing
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• v.5 no.1
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• pp.3-8
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• 1985

A three dimensional vision is obtained by stereoscopic view using a modified commercial TV set and matching color filter glasses. Two video signals from two CCTV cameras are connected to the RGB (red, green, blue) inputs of picture tube selecting two different colors for two video signals. A synchronizing signal drives a CCTV camera and the color TV set. On the other hand, a delayed synchronizing signal drives the other CCTV camera shifting its image on display. This shift is used in correcting image distortion.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.31-38
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• 2009

A process of identifying moving objects from data is typical task in many computer vision applications. In this paper, we propose a motion segmentation method that generally consists from background subtraction and foreground pixel segmentation. The Approximated Median Filter (AMF) was chosen to perform background modelling. To demonstrate the effectiveness of proposed approach, we tested it gray-scale video data as well as RGB color space.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.422-428
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• 2008

In this paper, we propose the robust object detection algorithm with spatial gradient information. To do this, first, we eliminate error values that appear due to complex environment and various illumination change by using prior methods based on hue and intensity from the input video and background. Visible shadows are eliminated from the foreground by using an RGB color model and a qualified RGB color model. And unnecessary values are eliminated by using the HSI color model. The background is removed completely from the foreground leaving a silhouette to be restored using spatial gradient and HSI color model. Finally, we validate the applicability of the proposed method using various indoor and outdoor conditions in a complex environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1147-1152
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• 2004

This paper presents the design of a multi-standard NTSC/PAL video encoder. The encoder converts International Telecommunication Union-Recommendation (ITU-R) BT.601 4:2:2, ITU-R BT.656 or RGB inputs from various video sources into National Television Standards Committee (NTSC) or phase-alternate line (PAL) TV signals in both S-video and composite video baseband signals (CVBS). The encoder adopts multiplier-free structures to reduce hardware complexity. The hardware bit width of programmable digital filters for luminance and chrominance signals, along with other operating blocks, are carefully determined to produce high-quality digital video signals of 1 least significant bit (LSB) error or less. The proposed encode. is experimentally demonstrated by using the Altera APEX20K600EBC652-3 device.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.9-16
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• 1997

This paper describes the design of a multistandard video encoder. The proposed encoder accepts conventional NTSC/PAL video signals, It also processes he PAL-plus video signal which is now popular in Europe. The encoder consists of five major building functions which are letter-box converter, color space converter, digital filters, color modulator and timing generator. In order to support multistandard video signals, a programmable systolic architecture is adopted in designing various digital filters. Interpolation digital filters are also used to enhance signal-to-noise ratio of encoded video signals. The input to the encoder can be either YCbCr signal or RGB signal. The outputs re luminance(Y), chrominance(C), and composite video baseband(Y+C) signals. The architecture of the encoder is defined by using Matlab program and is modelled by using Veriflog-HDL language. The overall operation is verified by using various video signals, such as color bar patterns, ramp signals, and so on. The encoder contains 42K gates and is implemented by using 0.6um CMOS process.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.415-416
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• 2006

In this paper, we proposed a new coding technique of digital hologram video using 3D scanning method and video compression technique. The proposed coding consists of capturing a digital hologram to separate into RGB color space components, localization by segmenting the fringe pattern, frequency transform using $M{\tiems}N$ (segment size) 2D DCT (2 Dimensional Discrete Cosine Transform) for extracting redundancy, 3D scan of segment to form a video sequence, motion compensated temporal filtering (MCTF) and modified video coding which uses H.264/AVC.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.