• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.20 no.1
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• pp.71-78
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• 1990

This research was made to investigate the change of the image layer and of the vertical and horizontal magnification on the Panelipse radiographic image by the control of profile index. Using the Panelipse, a series of 60 exposures were taken with the steel balls placed in the holes of the plastic model plate, and then evaluated by 4 observers. Two points were assigned for a reading of sharp, one for middling sharp, and zero for unsharp. Each ball image then could be given a total reader score of 0 to 8. The author analyzed the image layer as defined by a sharpness score of 6 or more. The results obtained were as follows: As the profile index was increased, the shape of the image layer was not changed, and the width of the image layer was increased, and the position of the layer shifted away from the rotation center. As the profile index was increased, the ranges of vertical and horizontal magnification was increased, especially the ranges of horizontal magnification was greater than that of vertical magnification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2913-2929
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• 2014

Traditional vector quantization (VQ) schemes encode image blocks as VQ indices, in which there is significant similarity between the image block and the codeword of the VQ index. Thus, the method can compress an image and maintain good image quality. This paper proposes a novel lossless VQ indices compression algorithm to further compress the VQ index table. Our scheme exploits the high correlation of adjacent image blocks to search for the same VQ index with the current encoding index from the neighboring indices. To increase compression efficiency, codewords in the codebook are sorted according to the degree of similarity of adjacent VQ indices to generate a state codebook to find the same index with the current encoding index. Note that the repetition indices both on the search path and in the state codebooks are excluded to increase the possibility for matching the current encoding index. Experimental results illustrated the superiority of our scheme over other compression schemes in the index domain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1C
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• pp.35-43
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• 2005

This paper introduces a new algorithm to improve compression performance of 256 color images called palette-based or indexed images. The proposed scheme counts each frequency of index values after present index value and determines each rank for every index value by sorting them in descending order. Then, the scheme makes ranked index image instead of original indexed image using the way to replace index values with ranks. In the ranked index image's distribution produced as a result of this algorithm, the higher ranked index value, the more present same values. Therefore, data redundancy will be raised and more efficient performance of compression can be expected. Simulation results verify that because of higher compression ratio by up to 22.5, this newly designed algorithm shows a much better performance of compression in comparison with the arithmetic coding, intensity-based JPEG-LS and palette-based GIF.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.1-11
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• 2021

Detection of surface water features including river, wetland, reservoir from the satellite imagery can be utilized for sustainable management and survey of water resources. This research compared the water indices derived from the multispectral bands and the machine learning technique for detecting the surface water features from he Landsat-8 satellite image acquired in Daegu through the following steps. First, the NDWI(Normalized Difference Water Index) image and the MNDWI(Modified Normalized Difference Water Index) image were separately generated using the multispectral bands of the given Landsat-8 satellite image, and the two binary images were generated from these NDWI and MNDWI images, respectively. Then SVM(Support Vector Machine), the widely used machine learning techniques, were employed to generate the land cover image and the binary image was also generated from the generated land cover image. Finally the error matrices were used for measuring the accuracy of the three binary images for detecting the surface water features. The statistical results showed that the binary image generated from the MNDWI image(84%) had the relatively low accuracy than the binary image generated from the NDWI image(94%) and generated by SVM(96%). And some misclassification errors occurred in all three binary images where the land features were misclassified as the surface water features because of the shadow effects.

• Journal of Families and Better Life
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• v.27 no.6
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• pp.1-12
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• 2009

The purpose of the study is to investigate developmental changes in the effect of sociocultural factors towards appearance, body mass index and self-esteem on body image. Participants were 315elementary school, 305middle school students, 310hight school students and 346college students from Seoul and Gyeonggi Province. Collected data were analyzed through Cronbach's $\alpha$, Two-way ANOVA, Pearson's correlation, and stepwise multiple regression. The findings of the study were as follows: 1) Sociocultural factors towards appearance, body mass index, self-esteem and body image differed by grade and gender. 2) Peers, self-esteem, BMI and mass media were significant predictors of elementary school students' body image. Mass media, BMI and self-esteem were significant predictors of middle school students' body image. Self-esteem, peers, BMI, gender and mass media were significant predictors of high school students' body image. Self-esteem, mass media and BMI were significant predictors of college students' body image.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.17-21
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• 2010

As the compact and easily accessible handheld devices, such as cellular phones and MP3 players equipped with image acquisition functionality, are becoming widely available among common users, various applications of images are rapidly increasing. Image related services and software such as web-based image presentation and image manipulation for personal or commercial purpose enable users to view contents of remote image archive and to manipulate enormous amount of images in local or network based storage as well. It is necessary for users to identify the images efficiently so that the same images are perceived as one physical entity instead of recognizing them as different images as the trends are getting stronger. In order to support this environment, we propose a method that generates image identifiers or indexing for images within a solid and efficient manner. The proposed image identifier utilizes multiple index values. The integration of component index values creates a unique composite value that can be used as a file name, file system identifier, or database index. Our experimental results on generation of constituent index values have shown favorable results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.993-1014
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• 2021

This paper proposes a new image retrieval method called the 3D integrated multi-index to fuse SIFT (Scale Invariant Feature Transform) visual words with other features at the indexing level. The advantage of the 3D integrated multi-index is that it can produce finer subdivisions in the search space. Compared with the inverted indices of medium-sized codebook, the proposed method increases time slightly in preprocessing and querying. Particularly, the SIFT, contour and colour features are fused into the integrated multi-index, and the joint cooperation of complementary features significantly reduces the impact of false positive matches, so that effective image retrieval can be achieved. Extensive experiments on five benchmark datasets show that the 3D integrated multi-index significantly improves the retrieval accuracy. While compared with other methods, it requires an acceptable memory usage and query time. Importantly, we show that the 3D integrated multi-index is well complementary to many prior techniques, which make our method compared favorably with the state-of-the-arts.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.658-665
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• 2005

Re-assignment scheme of index in index image is called reindexing. It has been well known that index image can be reindexed without losslessness. In this paper, we introduces an adaptive rank based reindexing scheme using co-occurrence frequency between neighboring pixels. Original index image can be converted into rank image by the proposed scheme. Using the proposed scheme, a better compression efficiency can be expected because most of the reindexed values(rank) get distributed with a smaller variance than the original index image. Experinental results show that the proposed scheme achieves a much better compression performance over GIF, arithmetic coding, Zeng's algorithm and RIAC scheme.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.613-624
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• 2003

This paper proposes a design for efficient and accurate retrieval of similar image subsequences using the multi-dimensional time warping distance as similarity evaluation tool in image sequence database after building of two indexing structures implemented with priority queue and suffix tree respectively. Receiving query image sequence, at first step, the proposed method searches the candidate set of similar image subsequences in priory queue index structure. If it can not get satisfied results, it retrieves another candidate set in suffix tree index structure at second step. The using of the low-bound distance function can remove the dissimilar subsequence without false dismissals during similarity evaluating process between query image sequence and stored sequences in two index structures.

• Korean Journal of Adult Nursing
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• v.24 no.2
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• pp.200-207
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• 2012

Purpose: The purpose of this study was to investigate the influences of body mass index (BMI), mindfulness and self-esteem on reported body image among university students. Methods: Data were collected through questionnaires from 266 students and were analyzed using descriptive statistics, t-test, ANOVA, Scheffe's test, Pearson's correlation coefficients and Stepwise multiple regression analysis with SPSS/WIN 19.0 program. Results: As defined by body mass index, the sample was divided into an underweight group was 88.7%, a normal weight group was 10.5%, and an overweight group was 0.8%. The levels of body image depended on family income, personality, and BMI. The body image was significantly correlated with BMI, mindfulness, and self-esteem. The influential factors affecting body image were self-esteem, BMI, family income and personality, which explained about 34.6% of the variance. Conclusion: The results of this study indicate that nursing intervention are needed to improve body image, and that such variables should be carefully considered in intervention for university students.