• Journal of the Korea Computer Graphics Society
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• v.24 no.3
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• pp.43-48
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• 2018

In this paper, we present a method for removing shadows from scanned documents. Compared to the existing methods such as one based on image pyramid representation or adaptive thresholding, our method produces more robust and higher quality results. The basic idea of the approach is to use the local image statistics and to separate interesting regions from the image such as the regions around letters and figures. For the separated regions, we adaptively adjust the local brightness and contrast, and apply the sigmoid function to the intensity values as well to enhance the clarity of the image. For separated the other empty regions, we apply the gradient-base image hole filling method to fill the region with smooth color change.

• Journal of the East Asian Society of Dietary Life
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• v.20 no.5
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• pp.639-654
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• 2010

This study attempted to research the local food of various regions at a personal level by discovering how food has developed das part of a region's culture base. Discovery of the characteristic story behind the making of a region's characteristic food as local delicacies can inspire self-esteem in the culture, and enhance the real-life image as appropriate to a region, and thereby be made a part of local tourism and thus contributing to the local economy. For this reason, the native foods of the region of Chungcheongnam-do were researched in terms of the cultural sensibilities that inform the unique history of that region. The study was designed so as to aid in understanding food's characteristic value in Chungcheongnam-do and to give a historical representation of Chungcheongnam-do's image by means of storytelling techniques; thus, the local food's character can be presented alongside a story that appeals to the five senses. For this purpose, Chungcheongnam-do's representative native rice table was cast as the 'Hyunchoong rice meal table' - after the figure of admiral Yi Sun Shin of Asan area region, a representative image of Chungcheongnam-do - and 'Choosa rice meal table', after the figure of 'Choosa' Kim Jeong Hee of Yesan region, of which various literary works form a representative image of Chungcheongnam-do. 'Hyunchoong rice meal table' was composed of a health food centered menu which could supply sufficient nutrition as a food ration in times of war or winter shortage, thus providing an image of nutrition and power as appropriate to these situations. Also, to assess the health effectiveness of each rice table, the functionality of the ingredients were investigated as reported in 'Sik-ryo-chan-yo : a dietary treatment' which was published by Soon-Ui Cheon in the Chosun era and by which the foods of the early Chosun era won recognition as being both healthy profitable.

• Journal of Agricultural Extension & Community Development
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• v.17 no.4
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• pp.827-849
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• 2010

The study aims to examine the brand image for developing place name and local brand to create effective development. The data were collected purposive sampling technique by face-to face interview. 154 of resident and 152 of visitor in Seocheon county were used for analysis. Collected data were analyzed by ANOVA and factor analysis. The study found that it was deducted as passionate, comfortable, conservative image through exploring factor analyze that was about brand image's individuality in Seocheon county. And, it had an order that was Konmoe (29.2%), Solli(20.8%), Soya(17.5%) on resident, Konmoe(30.9%), Solli(19.7%), Munitgol(16.4%) on visitor, in place name favorable degree of the nature village. Results suggest that place name be utilized by brand individuality for place marketing effectively.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2343-2346
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• 2003

The spatial resolution of multispectral images can be improved by merging them with higher resolution image data. A fundamental problem frequently occurred in existing fusion processes, is the distortion of spectral information. This paper presents a spatially adaptive image fusion algorithm which produces visually natural images and retains the quality of local spectral information as well. High frequency information of the high resolution image to be inserted to the resampled multispectral images is controlled by adaptive gains to incorporate the difference of local spectral characteristics between the high and the low resolution images into the fusion. Each gain is estimated to minimize the l$_2$-norm of the error between the original and the estimated pixel values defined in a spatially adaptive window of which the weight are proportional to the spectral correlation measurements of the corresponding regions. This method is applied to a set of co-registered Landsat7 ETM＋ panchromatic and multispectral image data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.83-86
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• 1995

Many image display devices allow only a limited number of colors to be simultaneously displayed. In displaying of natural color image using color palette, it is necessary to construct an optimal color palette and map each pixel of the original image to a color palette with fast. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. Same as the clustering process, original color image is mapped to palette color via a local region block centering around prequantized original color value. The proposed algorithm incorporated with a spatial activity weighting value which is smoothing region. The method produces high quality display images and considerably reduces computation time.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1108-1118
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• 2019

Non-local means (NLM) algorithm is an effective and successful denoising method, but it is computationally heavy. To deal with this obstacle, we propose a novel NLM algorithm with fuzzy metric (FM-NLM) for image denoising in this paper. A new feature metric of visual features with fuzzy metric is utilized to measure the similarity between image pixels in the presence of Gaussian noise. Similarity measures of luminance and structure information are calculated using a fuzzy metric. A smooth kernel is constructed with the proposed fuzzy metric instead of the Gaussian weighted L2 norm kernel. The fuzzy metric and smooth kernel computationally simplify the NLM algorithm and avoid the filter parameters. Meanwhile, the proposed FM-NLM using visual structure preferably preserves the original undistorted image structures. The performance of the improved method is visually and quantitatively comparable with or better than that of the current state-of-the-art NLM-based denoising algorithms.

• Journal of the Korea Concrete Institute
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• v.21 no.2
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• pp.121-127
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• 2009

The failure behavior of RC structure was exceedingly affected by the size and the local strain distribution of the failure zone due to the strain localization behavior on the tension softening materials. However, it is very difficult to quantify and assess the local strain occurring in the failure zone by the conventional test method. In this study, image processing technology, which is available to measure the strain up to the complete failure of RC structures, was used to estimate the local strain distribution and the size of failure zone. In order to verify the reliability and validity for the image processing technology, the strain transition acquired by the image processing technology was compared with strain values measured by the concrete gauge on the uniaxial compressive specimens. Based on the verification of image processing technology for the uniaxial compressive specimens, the size and the local strain distribution of the failure zone of deep beam was measured using the image processing technology. With the results of test, the principal tensile/compressive strain contours were drawn. Using the strain contours, the size of the failure zone and the local strain distribution on the failure of the deep beam was evaluated. The results of strain contour showed that image processing technology is available to assess the failure behavior of deep beam and obtain the local strain values on the domain of the post-peak failure comparatively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1760-1778
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• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.300-306
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• 2000

This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.