• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.30-39
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• 2021

Research in the field of health lighting has continued to advance to reproduce the color temperature of natural light which periodically changes. However, most of this research could only reproduce a uniform circadian color temperature of natural light, therefore failing to realize the characteristics of the circadian cycle of color temperature difference by latitude and longitude. To reproduce the color temperature of natural light on which the characteristics of a region are reflected, the collection technology of real-time characteristics of natural light is needed. If the color temperatures which are not within a periodical pattern due to climate changes, etc., are measured, it will be difficult to judge the occurrence (presence) of the anomalies and to reproduce the circadian cycle of the color temperature of natural light. Therefore, this study proposes an algorithm for judging the anomalies in real time based on the sliding window to reproduce the color temperature of natural light. First, the natural light characteristics DB collected through the on-site measurement were analyzed, the differential values at a one-minute interval were calculated and examined, and then representative color temperature circadian patterns by solar terms were drawn. The anomalies were then detected by the application of the sliding window that calculated the deviation of the color temperature for the measured color temperature data set, which was collected through RGB sensors, while moving along the time sequence. In addition, the presence of anomalies was verified through the comparison study between the detection results and the representative circadian cycle of the color temperature by solar term. The judgment method for the anomalies from the measured color temperature of natural light was proposed for the first time, confirming that the proposed method was capable of detecting the anomalies with an average accuracy of 94.6%.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of Advanced Navigation Technology
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• v.9 no.1
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• pp.48-55
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• 2005

In this paper, we propose an efficient moving object tracking technique for multi-camera surveillance system. Color CCD cameras used in this system are network cameras with their own IP addresses. Input image is transmitted to the media server through wireless connection among server, bridge, and Access Point (AP). The tracking system sends the received images through the network to the tracking module, and it tracks moving objects in real-time using color matching method. We compose two sets of cameras, and when the object is out of field of view (FOV), we accomplish hand-over to be able to continue tracking the object. When hand-over is performed, we use MHI(Motion History Information) based on color information and M-bin histogram for an exact tracking. By utilizing MHI, we can calculate direction and velocity of the object, and those information helps to predict next location of the object. Therefore, we obtain a better result in speed and stability than using template matching based on only M-bin histogram, and we verified this result by an experiment.

• Journal of the Korea Society of Computer and Information
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• v.18 no.6
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• pp.21-28
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• 2013

This paper proposes an effective fire detection approach that includes the following multiple heterogeneous algorithms: moving region detection using grey level histograms, color segmentation using fuzzy c-means clustering (FCM), feature extraction using a grey level co-occurrence matrix (GLCM), and fire classification using support vector machine (SVM). The proposed approach determines the optimal threshold values based on grey level histograms in order to detect moving regions, and then performs color segmentation in the CIE LAB color space by applying the FCM. These steps help to specify candidate regions of fire. We then extract features of fire using the GLCM and these features are used as inputs of SVM to classify fire or non-fire. We evaluate the proposed approach by comparing it with two state-of-the-art fire detection algorithms in terms of the fire detection rate (or percentages of true positive, PTP) and the false fire detection rate (or percentages of true negative, PTN). Experimental results indicated that the proposed approach outperformed conventional fire detection algorithms by yielding 97.94% for PTP and 4.63% for PTN, respectively.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.197-204
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• 2008

It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.507-515
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• 2009

In this paper, we propose an image signal processor (ISP) for an ultra small HD-grade video sensor with 3A (AWB, AE, and AF) in camera phones that can process 720P/30fps videos. In order to enhance the video quality of the systems, it is necessary to achieve the high performance of the 3A. The proposed AWB algorithm multiplies the adjusted coefficients of color gains to the captured data of white objects. The proposed AE method adopts the index step moving based on the difference between an averaged Y luminance and a target luminance, together with IIR filters with variable time responses. The proposed AF technique controls the focus curve to find the lens position that maximizes the integrated high frequency components in luminance values by using highpass filters. Finally, we compare the image quality captured from our system to the quality of a commercial HD camcorder in order to evaluate the performance of the proposed ISP. The proposed ISP system is also fabricated with 0.18um CMOS flash memory process.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.510-517
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• 2001

In this paper, we implement a real time speaker close-up system using lip motion information from input images having some people. After detecting a speaker from input moving pictures through one color CCD camera, the other camera closes up the speaker by using lip motion information. The implemented system detects a face and lip area of each person by means of a facial color and a morphological information, and then finds out a speaker by using lip area variation. A PTZ(Pan/Tilt/Zoom) camera is used in order to close up the detected speaker and it is controlled by RS-232C serial port. Consequently, we can exactly detect a speaker in input moving pictures including more than three people.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.111-113
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• 2012

KINECT is a gesture recognition camera produced by Microsoft Corp. KINECT SDK are widely available and many applications are actively being developed. Especially, KIET (Kinect Image Extraction Technique) has been used mainly for extracting moving objects from the input image. However, KIET has difficulty in extracting the human head due to the absorption of light. In order to overcome this problem, this paper proposes a new method for improving the KIET performance by using both color-image and depth image. Through experimental results, it is shown that the proposed method performs better than the conventional KIET algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.4 s.152
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• pp.554-566
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• 2006

The purpose of this paper is to understand the ethnic characteristics of official uniforms of Qing(淸)) by comparing the rank systems of official uniforms of Ming(명(明)) and Qing(淸)) dynasties. As research documents, Dai-Ming-Huidian(大明會典)) and Qing-Huidian-Tu(淸明會圖)) have been used. This research shows that there are many traditional characteristics of Manchurians (滿族)) in the official uniforms of Qing(淸)) dynasty. The characteristics are as follows: First, Qing dynasty made their own official uniform based on the traditional Manchurians(滿族)) costume, and added rank system on it. Second, Qing dynasty used the animal's leather as the material of official uniforms and distinguished the level of the uniforms according to the rerity value of rareness, color, and warmth of the leather. Third, Qing dynasty used pearls produced in Manchuria as the highest level, as opposed to jades and rhinoceros horns of Ming. Fourth, Qing dynasty eliminated the animal's rank system of twelve patterns which had been used for whole history of China, but the Emperor is the only man who is able to use twelve patterns. Qing dynasty made her own pattern system of standstill/moving dragons and standstill/moving pythons. Fifth, Qing dynasty used the rank system by colors in the order of yellow, red, and blue consistently over various official uniforms, while Ming used different color orders for different uniforms.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.2
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• pp.112-119
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• 2009

This paper describes a robust visual surveillance algorithm under outdoor environment. One of the difficult problems for outdoor is to obtain effective updating process of background images. Because background images generally contain the shadows of buildings, trees, moving clouds and other objects, they are changed by lapse of time and variation of illumination. They provide the lowering of performance for surveillance system under outdoor. In this paper, a robust algorithm for visual surveillance system under outdoor is proposed, which apply the mixture Gaussian filter and color invariant property on pixel level to update background images. In results, it was showed that the moving objects can be detected on various shadows under outdoor.