• Journal of Multimedia Information System
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• v.5 no.2
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• pp.87-90
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• 2018

Various approaches have been proposed to convert low dynamic range (LDR) to high dynamic range (HDR). Of these approaches, the Multi Scale Fusion (MSF) algorithm based on Laplacian pyramid decomposition is used in many applications and demonstrates its usefulness. However, the pyramid fusion technique has no means for controlling the luminance component because the total number of pixels decreases as the pyramid rises to the upper layer. In this paper, we extract the reflection light of the image based on the Retinex theory and generate the weight map by adjusting the reflection component. This weighting map is applied to achieve an MSF-like effect during image fusion and provides an opportunity to control the brightness components. Experimental results show that the proposed method maintains the total number of pixels and exhibits similar effects to the conventional method.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.837-847
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• 2016

Tone mapping for High Dynamic Range(HDR) image provides matching human visual perception between real world scene and displayable devices. Recently, a tone mapping algorithm based on localized gamma correction is proposed. This algorithm is using human visual properties of contrast and colorfulness with background intensity, generating a weight map for gamma correction. However, this method have limitations of controlling enhancement region as well as generating halo artifacts caused by the weight map construction. To overcome aforementioned limitations, proposed algorithm in this paper modifies previous weight map, considering base layer intensity of input luminance channel. By determining enhancement region locally and globally based on base layer intensity, gamma values are corrected accordingly. Therefore, proposed algorithm selectively enhances local brightness and controls strength of edges. Subjective evaluation using z-score shows that our proposed algorithm outperforms the conventional methods.

• Journal of the Korean Society of Food Culture
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• v.31 no.6
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• pp.634-642
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• 2016

Chinese cabbage is produced and consumed as a main material for kimchi and as a staple vegetable in Korea throughout the year. However, due to environmental changes unbalance between supply and demand is repeated annually, requiring development of long-term storage technologies. Chinese cabbages, were harvested, put in plastic boxes, and precooled at $2^{\circ}C$ for 24 hours using forced air precooler. After precooling, Chinese cabbages were MAP-treated with 0.02 mm HDPE film and functional film and stored at low temperature ($1{\pm}0.5^{\circ}C$). The weight-loss rates after 9-weeks of storage were 8.47% in the control group, 4.07% in the HDPE film-treated group, and 3.07% in the functional film-treated group, respectively, suppressing weight loss. Trimming loss rate after 6-weeks of storage was 6.86% in the functional film MAP-treated group and lower than 7.50% in the control group. In the sensory test with 7 points as the limit of commodity, the control group lost it after 6-weeks of storage while the MAP-treated groups retained over 7 points. The functional film MAP-treated group showed over 6 points for processing as kimchi until 9-weeks of storage, proving that Pallet-type MAP storage is effective for extending storage life of spring Chinese cabbage.

• 한국지형공간정보학회:학술대회논문집
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• 2005.08a
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• pp.61-72
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• 2005

The landslide risk assessment process consists of hazard risk assessment and vulnerability analysis. landslide hazard risk is location dependent. Therefore, maps and spatial technologies such as GIS are very important components of the risk assessment process. This paper discusses the advantages of using GIS technology in the risk assessment process and illustrates the benefits through case studies of live projects undertaken. The goal of this study is to generate a map of landslide vulnerability map by analysis of static natural factors with GIS. A simple and efficient algorithm is proposed to generate a landslide potentialities map from DEM and existing maps. The categories of controlling factors for landslides, aspect of slope, soil, vegetation are defined. The weight values for landslide potentialities are calculated from AHP method. Slope and slope-direction are extracted from DEM, and soil informations are extracted from digital soil map. Also, vegetation informations are extracted from digital vegetation map. Finally, as overlaying, landslide potentialities map is made out, and it is verified with landslide place.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.277-282
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• 2003

In this paper we propose Using Higher Order Neuron on the Supervised Learning Machine of the Kohonen Feature Map. The architecture of proposed model adopts the higher order neuron in the input layer of Kohonen Feature Map as a Supervised Learning Machine. It is able to estimate boundary on input pattern space because or the higher order neuron. However, it suffers from a problem that the number of neuron weight increases because of the higher order neuron in the input layer. In this time, we solved this problem by placing the second order neuron among the higher order neuron. The feature of the higher order neuron can be mapped similar inputs on the Kohonen Feature Map. It also is the network with topological mapping. We have simulated the proposed model in respect of the recognition rate by XOR problem, discrimination of 20 alphabet patterns, Mirror Symmetry problem, and numerical letters Pattern Problem.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.67-70
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• 2022

NLP 분야에서 적극 활용되기 시작한 Transformer 모델을 Vision 분야에서 적용하기 시작하면서 object detection과 segmentation 등 각종 분야에서 기존 CNN 기반 모델의 정체된 성능을 극복하며 향상되고 있다. 또한, label 데이터 없이 이미지들로만 자기지도학습을 한 ViT(Vision Transformer) 모델을 통해 이미지에 포함된 여러 중요한 객체의 영역을 검출하는 saliency map을 추출할 수 있게 되었으며, 이로 인해 ViT의 자기지도학습을 통한 object detection과 semantic segmentation 연구가 활발히 진행되고 있다. 본 논문에서는 ViT 모델 뒤에 classifier를 붙인 모델에 일반 학습한 모델과 자기지도학습의 pretrained weight을 사용해서 전이학습한 모델의 시각화를 통해 각 saliency map들을 비교 분석하였다. 이를 통해, 클래스 분류 학습 기반 전이학습이 transformer의 saliency map에 미치는 영향을 확인할 수 있었다.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.451-455
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• 2009

This paper provides a comparison of global path planning method in single string by using pulled and pushed SOFM (Self-Organizing Feature Map) which is a method among a number of neural network. The self-organizing feature map uses a randomized small valued initial-weight-vectors, selects the neuron whose weight vector best matches input as the winning neuron, and trains the weight vectors such that neurons within the activity bubble are move toward the input vector. On the other hand, the modified SOFM method in this research uses a predetermined initial weight vectors of the one dimensional string, gives the systematic input vector whose position best matches obstacles, and trains the weight vectors such that neurons within the activity bubble are move toward or reverse the input vector, by rising a pulled- or a pushed-SOFM. According to simulation results one can conclude that the modified neural networks in single string are useful tool for the global path planning problem of a mobile robot. In comparison of the number of iteration for converging to the solution the pushed-SOFM is more useful than the pulled-SOFM in global path planning for mobile robot.

• Food Science and Preservation
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• v.6 no.3
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• pp.264-269
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• 1999

The effects of film thickness and moisture absorbing materials(MAM) on the ginger qualities were investigated during MA storage for 150 days. LDPE films of 0.04, 0.06 and 0.08mm thicknesses were applied to select the adequate film in gas permiability. MAMs of sheet and sachet type were applied to 0.06mm-LDPE film bag to prevent moisture condensation during storage. Thickness of film used affected neither weight loss nor firmness of gingers during U storage. But the thinner in thickness showed the less changes in sprouting, spoilage and reducing sugar. Moreover, compared with MAP alone, MAPs with MAM of both sachet and sheet styles led to the weight loss of gingers increasing by more than 3-4 times, but sprouting rate, spoilage rate and reducing sugar decreasing by 3.3, 1.4 and 2.3 times, respectively. These results showed that MAP with UM was significantly effective to prolong the freshness of ginger by longer than 2 times, compared with MAP alone.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.47-54
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• 2005

The goal of this study is to generate a landslide potential map using GIS(Geographic Information System) based method. A simple and efficient algorithm is proposed to generate a landslide potentialities map from DEM(Digital Elevation Model) and existing maps. The categories of controlling factors for landslides, aspect of slope, soil, vegetation are defined. The weight value for landslide potentialities is calculated from AHP(Analytic Hierarchy Process) method. Slope and Slope-direction is extracted from DEM, and soil information is extracted from digital soil map. Also, vegetation information is extracted from digital vegetation map. Finally, as overlaying, landslide potentialities map is made out, and it is compared with landslide place.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.127-135
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• 2013

In order to acquire images in low-light environments, it is usually necessary to adopt long exposure times or resort to flash lights. However, flashes often induce color distortion, cause the red-eye effect and can be disturbing to subjects. On the other hand, long-exposure shots are susceptible to subject-motion, as well as motion-blur due to camera shake when performed hand-held. A recently introduced technique to overcome the limitations of traditional low-light photography is that of multi-spectral flash. Multi-spectral flash images are a combination of UV/IR and visible spectrum information. The general idea is that of retrieving details from the UV/IR spectrum and color from the visible spectrum. However, multi-spectral flash images themselves are subject to color distortion and noise. This works presents a method to compute multi-spectral flash images so that noise can be reduced and color accuracy improved. The proposed approach is a previously seen optimization method, improved by the introduction of a weight map used to discriminate uniform regions from detail regions. The weight map is generated by applying canny edge operator and it is applied to the optimization process for discriminating the weights in uniform region and edge. Accordingly, the weight of color information is increased in the uniform region and the detail region of weight is decreased in detail region. Therefore, the proposed method can be enhancing color reproduction and removing artifacts. The performance of the proposed method has been objectively evaluated using long-exposure shots as reference.