• 대한인간공학회지
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• 제21권1호
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• pp.95-112
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• 2002

Two experiments were carried out to compare the suitability in visual tasks between cathode-ray tube (CRT) and thin film transistor-liquid crystal display (TFT-LCD). In the first experiment, the subjects were requested to detect pre-assigned target words or icons among distracters presented under time-invariant (static) image mode. The subjects' visual performance and fatigue were assessed while carrying out search tasks with dim and bright ambient light conditions. Significant interaction effects were found among displays, task types, and ambient light conditions. Due to visual fatigue, the subjects' accommodative power decreased in the end of task and the degradation was more significant for the CRT users and under bright ambient light. IN the second experiment, the subjects performed information processing task with time-varying road signs at a driving simulator to assess interaction effects between display types and changing speed of dynamic image. The perception time using TFT-TCD was shorter under slow image change while that of CRT was shorter rapid image change. Findings from this study suggest that, to improve visual task performance, users should carefully select their visual display type depending on the task to be performed.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1877-1885
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• 2015

This paper presents a new Nearest-Neighbors based weighted representation for images and weighted K-Nearest-Neighbors (WKNN) classifier to improve the precision of image classification using the Bag of Visual Words (BOVW) based models. Scale-invariant feature transform (SIFT) features are firstly extracted from images. Then, the K-means++ algorithm is adopted in place of the conventional K-means algorithm to generate a more effective visual dictionary. Furthermore, the histogram of visual words becomes more expressive by utilizing the proposed weighted vector quantization (WVQ). Finally, WKNN classifier is applied to enhance the properties of the classification task between images in which similar levels of background noise are present. Average precision and absolute change degree are calculated to assess the classification performance and the stability of K-means++ algorithm, respectively. Experimental results on three diverse datasets: Caltech-101, Caltech-256 and PASCAL VOC 2011 show that the proposed WVQ method and WKNN method further improve the performance of classification.

• 한국실내디자인학회논문집
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• 제23권5호
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• pp.112-121
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• 2014

The purpose of this study is to develop the user-oriented housing interior space sensibility evaluation tools: The user-oriented housing interior space sensibility evaluation tools shall be developed through the systematic selection process of the extracted housing interior space images, which were linked with the adjectives of sensibility evaluation selected for the housing interior space preferred by the user from the specific words of the sensibility extracted to identify the characteristics of the user's sensibility which is recently being changed. In the results of analyzing the words of sensibility for the residential space preferred by the users with 48 pairs of adjectives. The user-oriented sensibility assessment tool was built by extracting 8 sensibility factors of 'cozy', 'practical' 'cheerful', 'traditional', 'unique', 'congenial', 'sensuous', and 'gorgeous' in the exploratory factor analysis. The image scale was constructed in two-dimensions of the sense of space and the type of space for the residential interior space images. The dimension of the 'sense of space' is explained by the axis of open-closed and the dimension of 'type of space, is explained by the axis of 'natural-artificial'. Such a structural model of the residential interior design attributes were divided into 8 groups. And the 42 images representing each group were selected and the user-oriented residential interior space image tool was built by adding user's selective elements.

• 대한공간정보학회지
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• 제10권5호
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• pp.45-51
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• 2002

The goal of image merging techniques are to enhance the resolution of low-resolution images using the detail information of the high-resolution images. Among the several image merging methods, wavelet-based image merging techniques have the advantages of efficient decorrelation of image bands and time-scale analysis. However, they have no regard for spatial information between the bands. In other words, multiresolution data merging methods merge the same information-the detail information of panchromatic image-with other band images, without considering specific characteristics. Therefore, a merged image contains much unnecessary information. In this paper, we discussed this 'mixing' effect and, proposed a method to classify the detail information of the panchromatic image according to the spatial and spectral characteristics, and to minimize distortion of the merged image.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.117-120
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• 2002

In this paper, we propose a new text watermarking method using space coding and PN sequence. A PN sequence generated from user message modifies the space between words in each line. The detection can be done without original text image using the average space with in the text. Experimental results show that proposed method has the invisible property and robustness to the attack such as the elimination of words in the text.

• 한국실내디자인학회논문집
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• 제21권1호
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• pp.220-227
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• 2012

After The Ramsar Convention took place in Korea in 2008, public interest in environment heightened, and the government has been allocating its budget for conserving our environment. Therefore, the present study focuses on eco-friendly spatial images particularly shown in ecological museums in Korea which recognizes the value of the environment and the ecology and tries to both protect them and alert people about it. The purpose of this study is proving what consist of eco-friendly spatial images by analyzing the expressive word of eco-friendly images and the image of space, providing a basic data for future space planning of ecological museums. To do this, the present study proceeds in three steps. First of all, the base of research in analyzing stage is firmly established by grasping general theories and terms regarding spatial image. As a second step, the composition and the characteristics of exhibition is clarified through on-spot investigation to provide comparative data for spatial image assessment in the future. Also through this step, we could understand how the exhibits are designed currently. In the last stage of research, expressive words regarding eco-friendly spatial images are extracted and used to analyze the spatial image of ecological museums. And the following three conclusions is deduced. First, the expressive words of eco-friendly spatial image that are extracted are as following: "healthy", "coexisting", "clean", "blending", "warm", "soft", "lively", "pure", "cool", "fresh ", "comfortable", "relaxed", "mild", "free", "harmonious", and "healing". As the second conclusion, color, and material, the formation which is an architectural factor did not have a great impact on forming eco-friendly image, but the color and the material did. The third conclusion was that the display with natural aspects actively utilized increased eco-friendly spatial image.

• 패션비즈니스
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• 제19권2호
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• pp.103-117
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• 2015

The purpose of this study was to examine the uniform image of Korean herbal cosmetic brands amongst Korean and Chinese consumers. This study would enable us to explore a BI strategy to enhance international competitiveness of Korean herbal cosmetics brands. The results were as follows. The key words of BI pursued by Sulwhasoo were dignified, novel, graceful, soft, gaily, natural, Korean, modern, and international. Korean people felt that the uniform was graceful and soft, which accorded with Sulwhasoo BI, but also it was trite and dingy, indicating a negative and opposing image. On the other hand, Chinese people felt that the uniform was dignified, novel, graceful, natural, modern, and international, indicating that it matched with Sulwhasoo BI. In The History of Whoo, the key words of BI pursued by the brand were precious, soft, gorgeous, gaily, and natural. The Koreans felt that the uniform was intelligent, and decent, but conversely, it was also austere and dingy, indicating a negative image. The Chinese felt that the uniform was common, hard, austere, dingy, and unnatural, indicating an opposing image to BI. Finally, a uniform design was developed to improve on its problems, establish The History of Whoo's brand identity, and its brand image. First of all, 'The Quintessence : noble passion' was set up as a developmental concept. The textiles, clothing, and accessories were designed using the symbolic elements from The History of Whoo as a motif. Uniforms were developed for spring, fall, and summer.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권8호
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• pp.742-751
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• 2005

본 논문은 단어 분류에 기반한 새로운 텍스트 영상 워터마킹 알고리즘을 제안한다. 간단한 특징을 이용하여 단어를 K개로 분류한다. 이웃한 몇 개의 단어들을 조합하여 세그먼트를 구성하고, 세그먼트에 속한 단어들의 부류에 의해 세그먼트 또한 분류된다. 각 세그먼트에 동일한 양의 신호가 삽입된다. 신호 삽입은 세그먼트 부류가 갖는 단어 간 공백의 통계값을 조작함으로써 이루어진다. 몇 가지 기준에 따라 기존 단어 이동 알고리즘과의 주관적인 비교가 제시된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권11호
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• pp.4534-4555
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• 2015

We propose a robust object cataloging method using multiple locally distinct heterogeneous features for aiding image retrieval. Due to challenges such as variations in object size, orientation, illumination etc. object recognition is extraordinarily challenging problem. In these circumstances, we adapt local interest point detection method which locates prototypical local components in object imageries. In each local component, we exploit heterogeneous features such as gradient-weighted orientation histogram, sum of wavelet responses, histograms using different color spaces etc. and combine these features together to describe each component divergently. A global signature is formed by adapting the concept of bag of feature model which counts frequencies of its local components with respect to words in a dictionary. The proposed method demonstrates its excellence in classifying objects in various complex backgrounds. Our proposed local feature shows classification accuracy of 98% while SURF,SIFT, BRISK and FREAK get 81%, 88%, 84% and 87% respectively.

• 센서학회지
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• 제33권2호
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• pp.78-85
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• 2024

We proposed a method for visual place recognition that represents images using objects as visual words. Visual words represent the various objects present in urban environments. To detect various objects within the images, we implemented and used a zero-shot detector based on a large-scale image language model. This zero-shot detector enables the detection of various objects in urban environments without additional training. In the process of creating histograms using the proposed method, frequency-based weighting was applied to consider the importance of each object. Through experiments with open datasets, the potential of the proposed method was demonstrated by comparing it with another method, even in situations involving environmental or viewpoint changes.