• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.360-372
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• 2007

We propose a fast inter-layer mode decision method by utilizing coding information of base layer upward its enhancement layer inscalable video coding (SVC), also called MPEG-4 part 10 Advanced Video Coding Amendment 3 or H.264 Scalable Extension (SE) which is being standardized. In this paper, when the motion vectors from the base layer have zero motion (0, 0) in inter-layer motion prediction or the Integer Transform coefficients of the residual between current MB and the motion compensated MB by the predicted motion vectors from the base layer are all zero, the block mode of the corresponding block to be encoded at the enhancement layer is determined to be the $16{\times}16$ mode. In addition, if the predicted mode of the MB to be encoded at the enhancement layer is not equal to the $16{\times}16$ mode, then the rate-distortion optimization is only performed on the reduced candidated modes which are same or smaller partitioned modes. Our proposed method exhibits the complexity reduction in encoding time up to 72%. Nevertheless, it shows negligible PSNR degradation and bit rate increase up to 0.25dB and 1.73%, respectively.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.396-404
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• 2014

The field of searching clothing, which is very difficult due to the nature of the informal sector, has been in an effort to reduce the recognition error and computational complexity. However, there is no concrete examples of the whole progress of learning and recognizing for cloth, and the related technologies are still showing many limitations. In this paper, the whole process including identifying both the person and cloth in an image and analyzing both its color and texture pattern is specifically shown for classification. Especially, deformable search descriptor, LBPROT_35 is proposed for identifying the pattern of clothing. The proposed method is scale and rotation invariant, so we can obtain even higher detection rate even though the scale and angle of the image changes. In addition, the color classifier with the color space quantization is proposed not to loose color similarity. In simulation, we build database by training a total of 810 images from the clothing images on the internet, and test some of them. As a result, the proposed method shows a good performance as it has 94.4% matching rate while the former Dense-SIFT method has 63.9%.

• Archives of design research
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• v.19 no.2 s.64
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• pp.121-128
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• 2006

The elements to enhance preference in symbol design are mainly related to consumers' response and aesthetic elements. Because certain aesthetic elements in design affect consumers' response and it is actually presented through (the different level of) preference. This study through surveying case studies examines whether a certain aesthetic element in symbol design gives rise to much preference. According to the result of study, high preference in symbolic design depends on high level of Rhythm, Balance, Harmony, Elaboration, Round, Gestalt, Organic, and Artificial/Natural among aesthetic elements. In comparison, it is founded that Simplicity/complexity, Objective/Abstract, depth, and symmetry should be designed at the moderate level, and proportion, repetition of elements be at the low level. Additionally(or Besides) this study makes out that symbol design cases with high preference have shapes from natural material or patterns of traditional culture, while cases with low preference have shapes from geometric figures. On the basis of these results, a guideline of symbol design could De offered(or suggested) to fit preference of consumers. But, this study is mostly concerned with only affect among emotional reactions of consumer in a scope of study, and is considered only in the aspect of form excluding color and texture.

• Korean Journal of Environment and Ecology
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• v.33 no.4
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• pp.472-480
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• 2019

Selection of the plant material for planting to reduce fine dust should comprehensively consider the visual characteristics, such as the shape and texture of the plant leaves and form of bark, which affect the adsorption function of the plant. However, previous studies on reduction of fine dust through plants have focused on the absorption function rather than the adsorption function of plants and on foliage plants, which are indoor plants, rather than the outdoor plants. In particular, the criterion for selection of fine dust reduction species is not specific, so research on the selection criteria for plant materials for fine dust reduction in urban areas is needed. The purpose of this study is to identify the priorities of eight indicators that affect the fine dust reduction by using the fuzzy multi-criteria decision-making model (MCDM) and establish the tree selection criteria for the urban planting to reduce fine dust. For the purpose, we conducted a questionnaire survey of those who majored in fine dust-related academic fields and those with experience of researching fine dust. A result of the survey showed that the area of leaf and the tree species received the highest score as the factors that affect the fine dust reduction. They were followed by the surface roughness of leaves, tree height, growth rate, complexity of leaves, edge shape of leaves, and bark feature in that order. When selecting the species that have leaves with the coarse surface, it is better to select the trees with wooly, glossy, and waxy layers on the leaves. When considering the shape of the leaves, it is better to select the two-type or three-type leaves and palm-shaped leaves than the single-type leaves and to select the serrated leaves than the smooth edged leaves to increase the surface area for adsorbing fine dust in the air on the surface of the leaves. When considering the characteristics of the bark, it is better to select trees that have cork layers or show or are likely to show the bark loosening or cracks than to select those with lenticel or patterned barks. This study is significant in that it presents the priorities of the selection criteria of plant material based on the visual characteristics that affect the adsorption of fine dust for the planning of planting to reduce fine dust in the urban area. The results of this study can be used as basic data for the selection of trees for plantation planning in the urban area.