• 한국의류학회지
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• 제21권1호
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• pp.194-205
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• 1997

The typical instrumental assessment of ununiform natural soils has been carried out by yellowing of the specimens instead of the surface reflectance or the calculated formula. However, the regular instrumental area of sample holder is necessary for the measure of yellowing. Therefore, this study attempted to apply image analysis which had full color image by scanning of one time without limitation of instrumental area. The test samples were analyzed pseudo and full color image. This paper evaluated soil with hue of yellowing and gradation of gray level with color image analysis. Then, it was studied propriety of image analysis with correlation of yellowing, hue and gray level. Ultimately, the proposed image analysis in this paper was advanced method against the typical instrumental assessment.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2007년도 7th International Meeting on Information Display 제7권2호
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• pp.1478-1481
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• 2007

This paper introduced a measurement method for image sticking based on human vision perception. Existing image sticking quantification method is mostly different from visible level by human perception. It takes a long time to measure image sticking which is degraded by time due to using a spot photometer, therefore many test samples could not be evaluated in a given short period of time in mass production line. However, the new measurement method in this paper is possible to evaluate a large quantity of samples in fast and high correlation with human perceptual level of image sticking.

• 한국초등과학교육학회지:초등과학교육
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• 제32권4호
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• pp.527-534
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• 2013

This study investigated elementary school teachers' understanding of the image formation by converging lens, pinholes camera, mirror and water. In each case teachers were asked to draw the ray diagram to indicate the position of the image. Teachers' ray diagrams were analyzed in accordance with the scientific process of image formation. Results of analysis showed that teacher's conceptions were classified into five levels for each situation. And most of the teachers were in level 3 and level 4 in each case. Because they had difficulties in the appling scientific conception(propagating path of light, diffused reflection from each object point, role of the eye, ray tracing) to finding location of image. Also most of teachers didn't know how to apply the law of reflection and refraction to each situation. The study finally discussed the teacher training program of the optical image.

• Journal of Computing Science and Engineering
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• 제8권2호
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• pp.65-77
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• 2014

To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.

• IEIE Transactions on Smart Processing and Computing
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• 제3권3호
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• pp.103-109
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• 2014

This study derived the inter-conversion matrices, which can be used in heterogeneous image transcoding between the compressed images using different transforms, such as the $8{\times}8$ block discrete cosine transform (BDCT) and the one-level discrete wavelet transform (DWT). Basically, to obtain the one-level DWT coefficients from $8{\times}8$ BDCT, inverse BDCT should be performed followed by forward DWT, and vice versa. On the other hand, if the proposed interconversion approach is used, only one inter-conversion matrix multiplication makes the corresponding transcoding possible. Both theoretical and experimental analyses showed that the amount of computation of the proposed approach decreases over 20% when the inter-conversion matrices are used under specific conditions.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• 응용통계연구
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• 제32권5호
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• pp.721-740
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• 2019

영상처리 분야에서 중요한 분야인 잡음 제거는 통계적인 접근이 필요하지만 잡음에 대한 특정한 분포를 가정하기 어려우며 지역적 특징을 반영하는 공간 필터는 소표본에 해당하므로 모수적인 방법으로 접근할 수 없다. 1차 영상 미분과 2차 영상 미분은 영상에 포함된 잡음 수준에 따라 확연한 차이를 보이며 캐니 에지 검출기를 사용하면 보다 명확히 알 수 있다. 잡음 수준을 통계적으로 확인하고자 Fligner-Killeen 검정을 진행하고 붓스트랩 방법을 사용하였으며 추정된 잡음의 수준을 베타분포의 누적분포함수를 이용하여 0과 1사이의 값을 갖도록 하였다. 본 연구에서는 영상에 포함된 잡음 수준을 고려하는 잡음 제거 알고리즘을 제시하고자 한다.

• 교육녹색환경연구
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• 제12권3호
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• pp.58-67
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• 2013

This study is to analyze the satisfaction and the image evaluation of landscape elements in outdoor space by types of the university campus. The results are as follows. 1) Out of outdoor elements at university campus, planting area, resting area, access road, and water feature are recognized as major landscape elements. Among them, planting area and access roads are evaluated low in terms of satisfaction levels, therefore, improvement on these elements are required. 2) In outdoor space image evaluation, university campus has image such as 'simple', 'clear', and 'safe'. By scale of universities, both 'A' university, which is the biggest in terms of size of campus, and 'B' university, which has a medium sized campus, have a positive image. However, 'C' university, which is the smallest in terms of size of campus, has a passive and negative image. 3) 6 factors are extracted through Factor Analysis for image evaluation. All of the universities show positive image in the categories of 'clarity' and 'familiarity', however, 'B' university and 'C' university show negative image in the category of 'scale'. 4) In Correlation Analysis between landscape elements satisfaction level and image evaluation, it is showed that the group of landscape facility becomes a relation factor of overall image evaluation. As a result, the higher satisfaction level goes, the better image evaluation of overall outdoor space at university campus is.

• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.17-26
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• 2012

This paper presents an image processing-based validation method for unrecognizable numbers in severely distorted license plate images which have been degraded by various factors including low-resolution, low light-level, geometric distortion, and periodic noise. Existing vehicle license plate recognition (LPR) methods assume that most of the image degradation factors have been removed before performing the recognition of printed numbers and letters. If this is not the case, conventional LPR becomes impossible. The proposed method adopts a novel approach where a set of reference number images are intentionally degraded using the same factors estimated from the input image. After a series of image processing steps, including geometric transformation, super-resolution, and filtering, a comparison using cross-correlation between the intentionally degraded reference and the input images can provide a successful identification of the visually unrecognizable numbers. The proposed method makes it possible to validate numbers in a license plate image taken under low light-level conditions. In the experiment, using an extended set of test images that are unrecognizable to human vision, the proposed method provides a successful recognition rate of over 95%, whereas most existing LPR methods fail due to the severe distortion.

• 한국생산제조학회지
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• 제19권4호
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• pp.562-569
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• 2010

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the blurring of magnified image. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the blurring of magnified image. As a result, the nearest neighbor interpolation, which is the most frequently applied algorithm for the existing image interpolation algorithm, shows that the identification of a magnified image is not possible. Therefore, this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson' curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter, this study will develop an interpolation algorithm that has an excellent improvement for the boundary of the image and continuous and flexible property by using the NURBS, Ferguson' complex surface, and Bezier surface used in CAD/CAM engineering based on the results of this study.