• Journal of Animal Science and Technology
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• v.49 no.2
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• pp.195-202
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• 2007

The growth traits in swine are economically important, which are measured by gain in weight during test period or by age of days to certain weight. However, the difference in growth rate due to individual performance and also other factors occurs. The more reasonable estimation of the measurements of these traits provides the less error in genetic evaluation of pigs. The data from 1,576 heads being weighed periodically of Gyungnam-heugdon(Berkshire) were analyzed to estimate the growth curve which is used to decide average daily gain and days to 90kg. It may not be possible to directly compare accuracy between the conventional methods and the alternative methods. However, the alternative methods by growth curve would be superior to the conventional methods not only in theoretical background, but also in acceptability for diverse factors such as breed, sex and age. The theoretical superiority of the alternative methods comes from estimation at same age in daily gain and calculation of additional days from measuring date to days to 90kg by growth curve of individual. Also this can be easily adopted in a computer system according to breed and sex.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.273-284
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• 2008

Movements are a critical ability to young children's whole development, including physical, social/emotional, and cognitive development. This paper proposes the method to estimate movements suitable for young children's body conditions. The proposed method extracts a silhouette in each frame of videos that are obtained by deploying two video cameras by compensating illuminations, removing background and conducting morphology operations. And we extract silhouette feature values: an area, the ratio of length to width, the lowest foot position, and 7 Hu moments. Also, the area and movements of sub-area are used as local features. For motion estimation, we used probability propagation of the features extracted from the front and side frames. The proposed estimation algorithm is demonstrated for seven movements, walking, jumping, hopping, bending, stretching, balancing, and turning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.398-405
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• 2005

The multiuser detection (MUD) based wireless receiver requires more accurate channel estimation than the single user detection (SUD) schemes such as Rake receiver, and hence the post processing is required for MUD to clean up the estimated channel coefficients by eliminating the noise only coefficients. The adaptive post processing method is proposed in order to provide more accurate channel responses and the power level of the background noise and interferences at the cost of the negligible processing delay compared to the conventional method based on the threshold test with the threshold value relative to the noise variance. The simulations are performed in 3GPP-TDD mode environment. The results show that the noise estimation error of the proposed method is maximum $10\%$, which is much smaller than $50\%$ maximum error of the conventional method.

• The Journal of the Korea Contents Association
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• v.8 no.9
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• pp.1-9
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• 2008

In this paper, we proposed automatic face detection and tracking which is robustness in rotation. To detect a face image in complicated background and various illuminating conditions, we used face skin color detection. we used Harris corner detector for extract facial feature points. After that, we need to track these feature points. In traditional method, Lucas-Kanade feature tracker doesn't delete useless feature points by occlusion in current scene (face rotation or out of camera). So we proposed the estimation function, which delete useless feature points. The method of delete useless feature points is estimation value at each pyramidal level. When the face was occlusion, we deleted these feature points. This can be robustness to face rotation and out of camera. In experimental results, we assess that using estimation function is better than traditional feature tracker.

• Journal of Ginseng Research
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• v.40 no.1
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• pp.90-96
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• 2016

Background: Knowledge on microclimate conditions under artificial shades in a ginseng field would facilitate climate-aware management of ginseng production. Methods: Weather data were measured under the shade and outside the shade at two fields located in Gochang-gun and Jeongeup-si, Korea, in 2011 and 2012 seasons to assess temperature and humidity conditions under the shade. An empirical approach was developed and validated for the estimation of leaf wetness duration (LWD) using weather measurements outside the shade as inputs to the model. Results: Air temperature and relative humidity were similar between under the shade and outside the shade. For example, temperature conditions favorable for ginseng growth, e.g., between $8^{\circ}C$ and $27^{\circ}C$, occurred slightly less frequently in hours during night times under the shade (91%) than outside (92%). Humidity conditions favorable for development of a foliar disease, e.g., relative humidity > 70%, occurred slightly more frequently under the shade (84%) than outside (82%). Effectiveness of correction schemes to an empirical LWD model differed by rainfall conditions for the estimation of LWD under the shade using weather measurements outside the shade as inputs to the model. During dew eligible days, a correction scheme to an empirical LWD model was slightly effective (10%) in reducing estimation errors under the shade. However, another correction approach during rainfall eligible days reduced errors of LWD estimation by 17%. Conclusion: Weather measurements outside the shade and LWD estimates derived from these measurements would be useful as inputs for decision support systems to predict ginseng growth and disease development.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.64-72
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• 2007

In this paper we proposed a combined active contour model and motion estimation-based object tracking technique. After assigning the initial contour, we find the object's boundary and update the initial contour by using object's motion information. In the following frames, similar snake algorithm is repeated to make continuously estimated object's region. The snake algerian plays a role in separating the object from background, while motion estimation provides object's moving direction and displacement. The proposed algorithm provides equivalently stable, robust, tracking performance with significantly reduced amount of computation, compared with the existing shape model-based algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.39-47
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• 2010

A research of image-based articulated pose estimation has some problems such as detection of human feature, precise pose estimation, and real-time performance. In particular, various methods are currently presented for recovering many joints of human body. We propose the novel numerical inverse kinematics improved with the UKF(unscented Kalman filter) in order to estimate the human pose in real-time. An existing numerical inverse kinematics is required many iterations for solving the optimal estimation and has some problems such as the singularity of jacobian matrix and a local minima. To solve these problems, we combine the UKF as a tool for optimal state estimation with the numerical inverse kinematics. Combining the solution of the numerical inverse kinematics with the sampling based UKF provides the stability and rapid convergence to optimal estimate. In order to estimate the human pose, we extract the interesting human body using both background subtraction and skin color detection algorithm. We localize its 3D position with the camera geometry. Next, through we use the UKF based numerical inverse kinematics, we generate the intermediate joints that are not detect from the images. Proposed method complements the defect of numerical inverse kinematics such as a computational complexity and an accuracy of estimation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.3
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• pp.38-47
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• 2008

A vehicle counting system at intersection is designed and implemented using analyzing a video stream from a camera. To separate foreground image from background, we compare three different methods, among which Li's method is chosen. Blobs are extracted from the foreground image using connected component analysis and the blobs are tracked by a blob tracker, frame by frame. The primary tracker use only the size and location of blob in foreground image. If there is a collision between blobs, the mean-shift tracking algorithm based on color distribution of blob is used. The proposed system is tested using real video data at intersection. If some huristics is applied, the system shows a good detection rate and a low error rate.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.733-739
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• 2012

In this paper, a smoke detection algorithm robust to brightness and color variations depending on time and weather is proposed. The proposed smoke detection algorithm specifies the candidate region using difference images of input and background images, determines smoke by comparing feature coefficients of Gaussian mixture model of difference images. Thresholds for specifying candidate region is divided by four levels according to average brightness and chrominance of input images. Clusters of Gaussian mixture models of difference images are aligned according to average brightness. Smoke is determined by comparing distance of Gaussian mixture model parameters. The proposed algorithm is implemented by media dedicated DSP. As results of experiments, it is shown that the proposed algorithm is effective to detect smoke with camera installed outdoor.

• Journal of Digital Convergence
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• v.10 no.1
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• pp.365-369
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• 2012

We propose a vision-based method that estimates train position and movement for railway monitoring in which we use a fuzzy classifier to determine train states. The proposed method employs frame difference and background subtraction for estimating train motion and presence, respectively. These features are used as the linguistic variables of the fuzzy classifier. Experimental results show that the proposed method can correctly estimate train position and movement. Therefore the method can be used for railway monitoring systems which estimate crowd density or protect safety.