• Journal of Korean Society of Forest Science
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• v.88 no.2
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• pp.133-141
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• 1999

The purposes of this study were to evaluate the present management policy of recreation forest under competitive environment with similar types of recreation areas like national parks and to suggest the effective management strategies, using a multidimensional scaling technique. Data were collected from 1200 residents of Seoul, Pusan, Taegu, Kwangju, and Taejon sampled by two stage cluster sampling method. There were some different perceptions between Seoul residents and the others, but most of the respondents perceived recreation forests as uncrowded natural areas with reasonable use fees. The results suggested the need for developing effective marketing strategies to have distinguishing images from national parks that have competitive.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.150-153
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• 2014

영상 표시 장치에서 대조 이미지의 왜곡 현상을 보완하기 위해 히스토그램 평활화(Histogram Equalization)와 플래토 평활화(Plateau Equalization)가 사용된다. 히스토그램 평활화(Histogram Equalization)를 이용하여 명암대비를 증가 시킬 경우 과도한 이미지의 밝기 변화에 따른 과포화 현상이 발생하며 실시간 시스템에서는 물체 추적에 왜곡 현상이 발생한다. 특히, 적외선 영상(infrared image)과 같이 명암비가 한쪽으로 치우쳐 있는 영상들을 명암비를 개선하기 위해서는 플래토 평활화(Plateau Equalization)와 같은 영상 개선 방법이 필수적이다. 플래토 평활화에서는 임계값을 사용하는 방법이 제시되고 있지만 실험에 의한 최적 임계값을 찾아내는 방식이며, 이 방법은 입력되는 새로운 영상마다 임계값을 실험에 의해 매번 반복해서 도출해야 문제점이 있다. 본 논문에서 제안하는 방법은 과포화 되는 이미지 영역의 문제를 해결하기 위해 제시하는 방법으로 히스토그램 평활화(Histogram Equalization)의 동적 분할하는 알고리즘에 근거하되, 입력 영상에따라 적응적으로 임계값을 설정하는 기법을 제안한다. 실험을 통해 제안하는 방법이 실시간 영상에서 기존의 동적분할 히스토그램에 비해 자연스럽게 명암비를 개선하여 과포화 되거나 중요한 정보를 누락하여 왜곡 되지 않게 자연스러운 화면을 재생하는 방법을 제안한다.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.25-34
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• 2017

Autoencoder is a type of deep learning method where input layer and output layer are the same, and effectively extracts and restores characteristics of input vector using constraints of hidden layer. In this paper, we propose methods of Autoencoders to remove a natural background image which is a noise to the CAPTCHA and recover only a numerical images by applying various autoencoder models to a region where one number of CAPTCHA images and a natural background are mixed. The suitability of the reconstructed image is verified by using the softmax function with the output of the autoencoder as an input. And also, we compared the proposed methods with the other method and showed that our methods are superior than others.

• Korean Journal of Environment and Ecology
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• v.9 no.2
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• pp.232-249
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• 1996

The purpose of this is to suggest objective basic data for the use development and conservation management of the national park through the quantitative analysis of the visual quality included in the physical environment of the Odaesan National Park, for this, spatial images structure of physical elements have been analyzed by factor analysis algorithm and degree of visual quality have been measured mainly by questionnaries. Result of this thesis can be summarized as follows. Factors covering the spatial image of the Odaesan National Park landscape have been found to be the pverall synthetic evaluation, physical, spatial, natural quality and, appeal factors such as the overall the synthetic evaluation, spatial and appeal yield high factor scores. As for the factors determining the degree of visual quality of clear of valley, peculiarity of configuration, natural of trail, harmony of suitable artificaial planting and temple.

• The Korean Journal of Applied Statistics
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• v.33 no.5
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• pp.603-614
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• 2020

This study focuses on the prediction and factors of apartment prices in Seoul using a convolutional neural networks (CNN) model that has shown excellent performance as a predictive model of image data. To do this, we consider natural environmental factors, infrastructure factors, and social economic factors of the apartments as input variables of the CNN model. The natural environmental factors include rivers, green areas, and altitudes of apartments. The infrastructure factors have bus stops, subway stations, commercial districts, schools, and the social economic factors are the number of jobs and criminal rates, etc. We predict apartment prices and interpret the factors for the prices by converting the values of these input variables to play the same role as pixel values of image channels for the input layer in the CNN model. In addition, the CNN model used in this study takes into account the spatial characteristics of each apartment by describing the natural environmental and infrastructure factors variables as binary images centered on each apartment in each input layer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.39-46
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• 2019

In this study, before system development for the elimination of foreign fish species, we propose an algorithm to classify fish species by training fish images with CNN. The raw data for CNN learning were directly captured images for each species, Dataset 1 increases the number of images to improve the classification of fish species and Dataset 2 realizes images close to natural environment are constructed and used as training and test data. The classification performance of four CNNs are over 99.97% for dataset 1 and 99.5% for dataset 2, in particular, we confirm that the learned CNN using Data Set 2 has satisfactory performance for fish images similar to the natural environment. And among four CNNs, AlexNet achieves satisfactory performance, and this has also the shortest execution time and training time, we confirm that it is the most suitable structure to develop the system for the elimination of foreign fish species.

• Cartoon and Animation Studies
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• s.39
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• pp.111-132
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• 2015

Although Rotoscoping technique has been used for a long time to mimic the natural and smooth motion since the early 20th century, its artistic value was devalued as tricks because it traces the already recorded images. But the fact that the rotoscoping images can cross the boundaries between animation and live action in an infinite integral freedom in the digital era became rather expansive new aesthetic possibilities of representation of the reality. In addition, Jonas Odell's animations such as (2010), (2008), (2006) are good example to prove that the rotoscoping images also can serve as means to enhance its narrative. This study is to analyze how rotoscoping images act as a unique role in relation with the narrative based on the said person's real stories and realistic images. I argue that his animated films constantly contain these three characteristics -Images to mediate Auditory sensitivity as a record of inner metaphysical reality, anonymous images to represent a specific existential character, and images that act as physical representation that holds the physical space/time and related memory. This reveals that rotoscoping images in this digital era went beyond reproduction for natural movements or special type of style. It rather suggests new layers of experience, and acquires new value in animation. I hope that this study could serve as a foundation to rediscover and re-position the value of rotoscoping images as well as good opportunity to introduce very talented swedish animation artist who already received global attention with his unique philosophical and aesthetic style.

• Journal of Korean Society of Forest Science
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• v.90 no.6
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• pp.747-755
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• 2001

This study was analyzed the destination image and tests of image value of forest region festival by segmenting the market. A field survey was conducted during the Acasia-Honey Festival days in Chilgok, the famous acasia-honey products place, from May 12-15, 2001. In this study, 20 image items on five-point Likert scale were examined through factor analysis using a sample of 394 visitors. Four factors were identified as follows : environment, behavior-facilities, festival programs, and products. The author observed if there were statistically significant differences of destination images between the first-time and the repeat visitors, between residents and non-residents, and between purchasers and non-purchasers of acasia-honey products. The results indicated that repeat visitors and residents group had a more positive image of behavior factor such as hospitality and information for festival. And, the author found that purchasers of acasia-honey products had more positive image of product as well as environment factor such as special atmosphere, nostalgia, natural attractions, local culture, and novelty. For these results, it is possible to conclude that local government must effectively provide the festival visitors with well-defined information such as festival contents and schedule, also, develop the programs involved unique attributes of forest region festival to improve festival image.

• Korean Institute of Interior Design Journal
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• no.17
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• pp.52-59
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• 1998

In the modern ages when the surroundings of a city has become firm and monotonous this study designed to suggest an direction towards creative approaches to space planning by analyzing the images of interior space with the introduction of natural expressions as an alternative to create original space in order to give vitality to the previous standardized space and to satisfy human beings psychological desire. The results of the analysis as a way of expressing direct indirect and eclectic images using nature a source of arts read that most of the natural expressions show perceptive images strongly that natural elements can become the elements of design in any form and that nature's images are expressed by not only natural and artificial materials. In conclusion natural expression in interior space does not have any fixed form of expression but gives a great deal of vocabulary to the image formation of interior space by stimulating being's sentiment with the spatial restructure of nature's own particular order of form.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.