• Journal of Animal Environmental Science
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• v.3 no.2
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• pp.105-113
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• 1997

The environment for pig production should be controlled according to a criterion based on the pig's thermoregulartory behavior. Quantifying the pig's thermoregulatroy behavior was needed to prepare a criterion based on the pig's thermoregulatory behavior. Therefore, this study was conducted to quantify the pig's thermoregulatory behavior. The raw images were acquired according to the pig's thermoregulatory behavior and they were processed to binary images. The mean deviations of x and y coordinates of pig's images in a binary image were computed and they were multiplied. The values computed in this manner showed very wide differences according to the pig's thermoregulatory behavior. Therefore, the image processing and mean deviation can be certainly used as a method for classifying the pig's thermoregulatory behavior.

• Journal of Animal Environmental Science
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• v.5 no.2
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• pp.93-100
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• 1999

Pig's original image data was transformed to a binary image, an image excluding head and tail portion from the whole binary image, and a projected image associated with pig's height. Then the length of body, width of shoulder, and area of pig were calculated and the relationships among the above characteristics and pig's weight were analyzed. The results obtained from this study were as follows: 1. Whole binary image data was considered to be improper to determine the pig's weight because the movement of pig's head and tail portion affected the image data. 2. Binary image data excluding head and tail portion from the whole binary image showed a better estimation of the pig's weight than the whole binary image. 3. Pig's should width was analyzed to be improper factor to determine the pig's weight. 4. The projected image associated with pig's height showed the highest correlation between the pig's area of the image and pig's weight(R2=0.9965). From this research the projected image associated with pig's height, which is excluding head and tail portion from the whole body of pig's image, was considered to be the prime factor to measure the pig's weight by the noncontact measurement.

• Journal of Environmental Science International
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• v.11 no.8
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• pp.765-771
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• 2002

The current study investigated the relationship between image processed data and human visibility data for natural forest scenes from the perspective of color. In particular, the results indicated relatively low Pearson product-moment correlations between the color ratings obtained from the two methods used in the study. The first method measured the color content of slides using a image processing program, while the second used a panel of human judges to rate the color content of each slide.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.452-455
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• 2007

3D stereoscopic viewing of large scale imagery, such as aerial photography and satellite images, needs different parallaxes relative to the display scale. For example, when a viewer sees a stereoscopic image of aerial photography, the optimal parallax of its zoom-in image should be smaller than that of its zoom-out. Therefore, relative parallax adjustment according to the display scale is required. Merely adjusting the spacing between stereo images is not appropriate because the depths of the whole image are either exaggerated or reduced entirely. This paper focuses on the improving stereoscopic viewing with a single remote sensing image and a digital surface model (DSM). We present the parallax adjustment technique to maximize the 3D realistic effect and the visual comfort. For remote sensing data, DSM height value can be regarded as disparity. There are two possible kinds of methods to adjust the relative parallax with a single image performance. One is the DSM compression technique: the other is an adjustment of the distance between the original image and its stereo-mate. In our approach, we carried out a test to evaluate the optimal distance between a single remote sensing image and its stereo-mate, relative to the viewing scale. Several synthetic stereo-mates according to certain viewing scale were created using a parallel projection model and their anaglyphs were estimated visually. The occlusion of the synthetic stereo-mate was restored by the inpainting method using the fields of experts (FoE) model. With the experiments using QuickBird imagery, we could obtain stereoscopic images with optimized parallax at varied display scales.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.166-172
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• 2007

Egg quality indices are related with freshness, size of air chamber, loss of weight, and viscosity of the yolk and the protein. However, since the described quality parameters require measured in a destructive way, it is not suitable to inspect the egg quality with complete enumeration. Therefore, this study was performed to investigate the potential of image analysis method for evaluation of internal egg quality. Samples of 90 fresh eggs were collected immediately after laying and stored up to 24 days. Five eggs were randomly drawn from each storage condition (packing vs unpacking) at a regular interval and loss of weight, specific gravity and size of air chamber were measured. The image analysis for nondestructive measurement of size of air chamber was also studied. Results showed that the egg weight and gravity gradually decreased with increasing of storage days, while the size of air chamber linear increased caused by evaporation of water through the shell. A relationship a between conventional method and the image analysis method for measuring the size of air chamber was developed with the correlation coefficient of 0.928. The new finding implied that image analysis might provide a useful nondestructive tool to assess internal egg quality.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.557-567
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• 2015

With the increasing demands of 3D spatial information in urban environment, the importance of point clouds generation techniques have been increased. In particular, for as-built BIM, the point clouds with the high accuracy and density is required to describe the detail information of building components. Since the terrestrial LiDAR has high performance in terms of accuracy and point density, it has been widely used for as-built 3D modelling. However, the high cost of devices is obstacle for general uses, and the image-based 3D reconstruction technique is being a new attraction as an alternative solution. This paper compares the image-based 3D reconstruction technique and the terrestrial LiDAR in point of establishing the as-built BIM of outdoor structures. The point clouds generated from the image-based 3D reconstruction technique could roughly present the 3D shape of a building, but could not precisely express detail information, such as windows, doors and a roof of building. There were 13.2~28.9 cm of RMSE between the terrestrial LiDAR scanning data and the point clouds, which generated from smartphone and DSLR camera images. In conclusion, the results demonstrate that the image-based 3D reconstruction can be used in drawing building footprint and wireframe, and the terrestrial LiDAR is suitable for detail 3D outdoor modeling.

• Journal of the Korean Society of Costume
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• v.60 no.7
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• pp.61-73
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• 2010

This study aims to develop an fashion color design system based on personal color and sensorial images. This web-based system has a parallel structure which a user can search her own personal color, sensorial, and fashion images. The fashion image was presented according to the type of personal color image and sensorial image: futuristic fashion image from alluring image on all of personal color images; elegant fashion images from calm with pure/splendid images or faint/calm with alluring images; modern fashion image from pure/calm with alluring images or faint with lively images; plain fashion image from plain images with all personal color images but pure image; romantic fashion image from calm image with all personal color images but calm image. Fashion color and color combination palettes based on personal color images were presented with the each of those fashion images.

• Journal of the Korean Institute of Landscape Architecture
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• v.13 no.1
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• pp.109-121
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• 1985

A study on the image identification of urban streetscape is valuable for illuminating identity that is not yet fully approached in the field of environmental design. This analysis of urban streetscape for image identification allows us to make a more detailed exploration of an important approaching methods in dealing with the structural characteristics of identity. As a matter of fact, the earlier indirect studies on this image identification were made by environmental designers, such as architectural and urban designer in the field of environmental perception and came to its environmental cognition & environmental pattern research with assistances by such researchers as K. Lynch A. Rapoport & Christopher Alexander. Through its environmental perception research, we can see its structural characteristics that is aesthetic & visual structural contents of physical environmental elements. And we can see its cognitive characteristics through the environmental cognitive research, that is continuity, territoriality, identity of place, uniqueness or individuality, meaning & symbolism. Through its environmental pattern research, we can see its physical, socio - economic, cultural and symbolic pattern identification contents, that is physical form of the city, style of the street, pattern of streetscape, socio- economic & geographical locality, arid life cycle, life style, common style of the behavior, cultural pattern of the activity, socio - cultural expression of the symbol. In these process, we can set up a set of the environmental design criterias from those three integral studies for identity. And for an environmental research, Tongsung-Ro around the CBD (central business district) in Taegu City was selected for a case study, because this streetscape is suitable for that approaching methods in this study.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.345-349
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• 2005

Massive amount of satellite image processing such asglobal/continental-level analysis and monitoring requires automated and speedy georegistration. There could be two major automated approaches: (1) rigid mathematical modeling using sensor model and ephemeris data; (2) heuristic co-registration approach with respect to existing reference image. In case of ETM+, the accuracy of the first approach is known as RMSE 250m, which is far below requested accuracy level for most of satellite image processing. On the other hands, the second approach is to find identical points between new image and reference image and use heuristic regression model for registration. The latter shows better accuracy but has problems with expensive computation. To improve efficiency of the coregistration approach, the author proposed a pre-qualified matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with correlation coefficient. Throughout the pre-qualification approach, the computation time was significantly improved and make the registration accuracy is improved. A prototype was implemented and tested with the proposed algorithm. The performance test of 14 TM/ETM+ images in the U.S. showed: (1) average RMSE error of the approach was 0.47 dependent upon terrain and features; (2) the number average matching points were over 15,000; (3) the time complexity was 12 min per image with 3.2GHz Intel Pentium 4 and 1G Ram.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.837-856
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• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.