• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.463-466
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• 2010

In this paper, CCTV based fire surveillance system should aim to development. Advantages and Disadvantages analyzed of Existing sensor-based fire surveillance system and video-based fire surveillance system. To national support U-City, U-Home, U-Campus, etc, spread the ubiquitous environment appropriate to fire surveillance system model and a fire judgement technology. For this study, Microsoft LifeCam VX-1000 using through the capturing images and analyzed for apple and tomato, Finally we used H.264. The client uses the Linux OS with ARM9 S3C2440 board was manufactured, the client's role is passed to the server to processed capturing image. Client and the server is basically a 1:1 video communications. So to multiple receive to video multicast support will be a specification. Is fire surveillance system designed for multiple video communication. Video data from the RGB format to YUV format and transfer and fire detection for Y value. Y value is know movement data. The red color of the fire is determined to detect and calculate the value of Y at the fire continues to detect the movement of flame.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1491-1494
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• 2002

The paper introduces a novel system of two hands real-time tracking based on the unrestricted hand skin segmentation by multi color systems. After corer-based segmentation and pre-processing operation, a label set of regions is created to locate the two hands automatically. By the normalization, template matching is used to find out the left or right hand. An improved fast self-adaptive tracking algorithm is applied and Canny filter is used for hand detection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.213-224
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• 2009

This paper presents a new algorithm for estimating a driver's physical condition using real-time vision system and performs experimentation for real facial image data. The system relies on a face recognition to robustly track the center points and sizes of person's two pupils, and two side edge points of the mouth. The face recognition constitutes the color statistics by YUV color space together with geometrical model of a typical face. The system can classify the rotation in all viewing directions, to detect eye/mouth occlusion, eye blinking and eye closure, and to recover the three dimensional gaze of the eyes. These are utilized to determine the carelessness and drowsiness of the driver. Finally, experimental results have demonstrated the validity and the applicability of the proposed method for the estimation of a driver's physical condition.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.107-115
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• 2014

Visibility of the road influence the safe driving because it recognizes the obstacle on the road. In this paper, we propose a mobile data acquisition and processing system for evaluating road visibility at night. And it was converted efficiently with mobile images and archived for spatial analysis of road-visibilities at night. This was applied to the following techniques to the system. Low-power computing units, open an image processing library, GPU-based acceleration techniques and document database techniques, etc. And converting the RGB image to the YUV color system, which was integrated the brightness component and the spatial information. High performance Android devices were used to collect brightness data on roads and it was confirmed whether this prototype was to determine the spatial distribution of such acquisition and management systems for spatial-assessments of road visibility at night.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.287-293
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• 2014

Early fire detection is very important to avoid loss of lives and material damage. The conventional smoke detector sensors have difficulties in detecting smoke in large outdoor areas. The video-based smoke detection can overcome these drawbacks. This paper proposes a new smoke detection method in video sequences. It uses the ratio of variation rate of subband energy in the wavelet transform domain. In order to reduce the false alarm, candidate smoke blocks are detected by using motion, decrease of chromaticity and the average intensity of block in the YUV color space. Finally, it decides whether the candidate smoke blocks are smokes or not by using their temporal changes of subband energies in the wavelet transform domain. Experimental results show that the proposed method noticeably increases the accuracy of smoke detection and reduces false alarm compared with the conventional smoke detection methods using wavelets.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.9
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• pp.71-78
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• 2008

In this paper, we implement the H.264/AVC baseline decoder by hardware-software partitioning under the embedded Linux Kernel 2.4.26 and the FPGA-based target board with ARM926EJ-S core. We design several IPs for the time-demanding blocks, such as motion compensation, deblocking filter, and YUV-to-RGB and they are communicated with the host through the AMBA bus protocol. We also try to minimize the number of memory accesses between IPs and the reference software (JM 11.0) which is ported in the embedded Linux. The proposed IPs and the system have been designed and verified in several stages. The proposed system decodes the QCIF sample video at 2 frame per second when 24MHz of system clock is running and we expect the bitter performance if the proposed system is designed with ASIC.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.5
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• pp.24-30
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• 2010

In this paper, we described intra prediction which is the one of techniques to be used for higher compression performance in H.264/AVC and proposed the design of intra predictor for efficient intra prediction mode processing. The proposed system is consist of processing elements, precomputation processing elements, an intra prediction controller, an internal memory and a register controller. The proposed system needs the reduced the computation cycles by using processing elements and precomputation processing element and also needs the reduced the number of access time to external memory by using internal memory and registers architecture. We designed the proposed system with Verilog-HDL and verified with suitable test vectors which are encoded YUV files. The proposed architecture belongs to the baseline profile of H.264/AVC decoder and is suitable for portable devices such as cellular phone with the size of $176{\times}144$. As a result of experiment, the performance of the proposed intra predictor is about 60% higher than that of the previous one.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.241-246
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• 2016

Nowadays many people have an interest in facial expression and the behavior of people. These are human-robot interaction (HRI) researchers utilize digital image processing, pattern recognition and machine learning for their studies. Facial feature point detector algorithms are very important for face recognition, gaze tracking, expression, and emotion recognition. In this paper, a cascade facial feature point detector is used for finding facial feature points such as the eyes, nose and mouth. However, the detector has difficulty extracting the feature points from several images, because images have different conditions such as size, color, brightness, etc. Therefore, in this paper, we propose an algorithm using a modified cascade facial feature point detector using a convolutional neural network. The structure of the convolution neural network is based on LeNet-5 of Yann LeCun. For input data of the convolutional neural network, outputs from a cascade facial feature point detector that have color and gray images were used. The images were resized to $32{\times}32$. In addition, the gray images were made into the YUV format. The gray and color images are the basis for the convolution neural network. Then, we classified about 1,200 testing images that show subjects. This research found that the proposed method is more accurate than a cascade facial feature point detector, because the algorithm provides modified results from the cascade facial feature point detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6C
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• pp.450-458
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• 2008

In this paper, we propose a real-time stereoscopic display system based on H.264/AVC. We initially acquire stereo-view images from stereo web-cam using OpenCV library. The captured images are converted to YUV 4:2:0 format as a preprocess. The input files are encoded by stereo-encoder, which has a proposed estimation structure, with more than 30 fps. The encoded bitstream are decoded by stereo-decoder reconstructing left and right images. The reconstructed stereo images are postprocessed by stereoscopic image synthesis technique to offer users more realistic images with 3D effect. Experimental results show that the proposed system has better encoding efficiency compared with using a conventional stereo CODEC(coder and decoder) and operates with real-time processing and low complexity suitable for an application with a mobile environment.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.809-818
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• 2007

In this thesis, the color information is used to extract the traffic sign territory, and for recognizing the extracted image, it proposes the traffic sign recognition system that applies the error back propagation algorithm. The proposed method analyzes the color of traffic sign to extract and recognize the possible territory of traffic sign. The method of extracting the possible territory is to use the characteristics of YUV, YIQ, and CMYK color space from the RGB color space. Morphology uses the geometric characteristics of traffic sign to make the image segmentation. The recognition of traffic signs can be recognized by using the error back propagation algorithm. As a result of the experiment, the proposed system has proven its outstanding capability in extraction and recognition of candidate territory without the influence of differences in lighting and input image in various sizes.