• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.562-566
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• 2009

In this paper, we present a novel system to categorize web image search results using emotional concepts and to browse the results more conveniently and easily. The proposed system can categorize search results into 8 emotional categories based on emotion vector, which obtained by color and pattern features. Here, we use Kobayashi’s emotional categories: {romantic, natural, casual, elegant, chic, classic, dandy and modern}. With search results for a given query, the proposed system can provide categorized images for each emotional category. With 1,000 Yahoo! search images, we compared the proposed method with Yahoo! image search engine in respect of satisfaction, efficiency, convenience and relevance with a user study. Our experimental results show the effectiveness of the proposed method.

• Journal of Advanced Navigation Technology
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• v.20 no.4
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• pp.380-385
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• 2016

Shadows are common phenomena observed in natural scenes and often bring a major problem that is affected negatively in colour image analysis. It is important to detect the shadow areas and should be considered in the pre-processing of computer vision. In this paper, the method of shadow detection is proposed using cross entropy and intensity image, and is performed in single image based on the satellite images. After converting the color image to a gray level image, the shadow candidate region has been estimated the optimal threshold value by cross entropy, and then the final shadow region has been detected using intensity image. For the validity of the proposed method, the satellite images is used to experiment. Some experiments are conducted so as to verify the proposed method, and as a result, shadow detection is well performed.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.191-194
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• 2003

In this paper, we propose a new accurate and robust image mosaic technique of the mural underdrawing taken from the infra-red camera, which is based on multiple image registration and adaptive blending technique. The image mosaicing methods which have been developed so far have the following deficits. It is hard to generate a high resolution image when there are regions that do not have features or intensity gradients, and there is a trade-off in overlapping region site in view of registration and blending. We consider these issues as follows. First, in order to mosaic Images with neither noticeable features nor intensity gradients, we use a Projected supplementary pattern and pseudo color image for features in the image Pieces which are registered. Second, we search the overlapping region size with minimum blending error between two adjacent images and then apply blending technique to minimum error overlapping region. Finally, we could find our proposed method is more effective and efficient for image mosaicing than conventional mosaic techniques and also is more adequate for the application of infra-red mural underdrawing mosaicing. Experimental results show the accuracy and robustness of the algorithm.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.1-12
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• 2014

The purpose of this paper is to provide a compact overview of the state-of-art image mosaic algorithms in commercial softwares and to propose objective assessment method of that. Among them, several algorithms, widely used and high quality, result in the mosaic image by applying to seven different kinds of seasons of KOMPSAT-2 images and then consequently each result is analyzed visually. Moreover, quality index is suggested to assess the similarity with colors regarding adjacency images and then it is performed by comparing and analyzing the visual and quantitative results. Consequently, we found out the suggested quality index is feasible.

• The Korean Fashion and Textile Research Journal
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• v.15 no.6
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• pp.851-861
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• 2013

This study analyzed the fashionable characteristics of functional fashion mask types. This study reviewed the literature on masks and analyzed fashion photos found in fashion books, fashion collections and on internet fashion sites. The results were categorized into four characteristics. Integration of structure and function showed mask designs that connected to the hood and portable items. It represented the reflection of nomadic life, liberation, obscurity and the consciousness of discomfort. Signs of playfulness showed mask hybrids and animal images, the mask hybrids and humanoid images, the printing of animal characters, body parts and unusual material hybrids. It represented the liberation from a fixed identity, the loss of seriousness, the reduction of tension and the pursuit of pleasure and freedom. The duplicity of aggression and protection showed a futuristic or aggressive helmet facemask, an enclosed mask of intensive color, and the morphological hybrid of a disgusting or aggressive motif. It represented the end of human weakness, the desire of new self-expression and the longing of superhuman power. Fanciful decoration showed masks with glittery decoration, sunglasses with luxury decoration material, a medical facemask made of lace material and fanciful printing. It showed one facet of extreme consumption, the creation of new personality and value, the pursuit of high quality and a mutual coexistence of status and anonymity.

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.1188-1193
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• 2013

In content based image retrieval (CBIR) system, the images are represented based upon its feature such as color, texture, shape, and spatial relationship etc. In this paper, we propose a MRI Image Retrieval using wavelet transform with mahalanobis distance measurement. Wavelet transformation can also be easily extended to 2-D (image) or 3-D (volume) data by successively applying 1-D transformation on different dimensions. The proposed algorithm has tested using wavelet transform and performance analysis have done with HH and $H^*$ elimination methods. The retrieval image is the relevance between a query image and any database image, the relevance similarity is ranked according to the closest similar measures computed by the mahalanobis distance measurement. An adaptive similarity synthesis approach based on a linear combination of individual feature level similarities are analyzed and presented in this paper. The feature weights are calculated by considering both the precision and recall rate of the top retrieved relevant images as predicted by our enhanced technique. Hence, to produce effective results the weights are dynamically updated for robust searching process. The experimental results show that the proposed algorithm is easily identifies target object and reduces the influence of background in the image and thus improves the performance of MRI image retrieval.

• Cartoon and Animation Studies
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• s.12
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• pp.87-102
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• 2007

Animation techniques that can freely create any movement of color and shape produce strong attraction by visualizing fantasy. Like animation, fantasy is often misunderstood that it has nothing to do with reality, but it is not the case. Fantasy introduces a little confusion in our symbolic order by reorganizing elements from reality and commonness. This confusion, which becomes desire, induces attraction. However, the confusion beyond our comprehension creates total chaos in which we cannot be interested. Attraction happens only when the introduced confusion is far less than the total symbolic order which has already been established. The images of animation are neither completely mundane to us nor beyond our comprehension; thus, animation produces attraction by offering us images that stimulate our unconscious desire.

• Korean Journal of Geomatics
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• v.3 no.1
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• pp.59-65
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• 2003

The merging of different scales or multi-sensor image data is becoming a widely used procedure of the complementary nature of various data sets. Ideally, the merging method should not distort the characteristics of the high-spatial and high-spectral resolution data used. To present an effective merging method for survey of reclaimed land using the high-resolution (6.6 m) Electro-Optical Camera (EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1 (KOMPSA T-l) and the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) image data, this paper compares the results of Intensity Hue Saturation (IHS) and Principal Component Analysis (PCA) methods. The comparison is made by statistical and visual evaluation of three-color combination images of IHS and PCA results based on spatial and spectral characteristics. The use of MODIS bands 1, 2, and 3 with a contrast stretched EOC panchromatic image as a substitute for intensity was found to be particularly effective in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1424-1440
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• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1024-1033
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• 2016

In this study, a system is proposed for analyzing whether driver's eyes are open or closed on the basis of images to determine driver's drowsiness. The proposed system converts eye areas detected by a camera to a color space area to effectively detect eyes in a dark situation, for example, tunnels, and a bright situation due to a backlight. In addition, the system used a thickness distribution of a detected eye area as a feature value to analyze whether eyes are open or closed through the Support Vector Machine(SVM), representing 90.09% of accuracy. In the experiment for the images of driver wearing glasses, 83.83% of accuracy was obtained. In addition, in a comparative experiment with the existing PCA method by using Eigen-eye and Pupil Measuring System the detection rate is shown improved. After the experiment, driver's drowsiness was identified accurately by using the method of summing up the state of driver's eyes open and closes over time and the method of detecting driver's eyes that continue to be closed to examine drowsy driving.