• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.561-571
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• 2019

In this paper, we analyze the effect of the representative spectral indices, normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI) on classification accuracies of Landsat-8 OLI image.After creating these spectral index images, we propose five methods to select the spectral index images as classification features together with Landsat-8 OLI bands from 1 to 7. From the experiments we observed that when the spectral index image of NDVI or NDWI is used as one of the classification features together with the Landsat-8 OLI bands from 1 to 7, we can obtain higher overall accuracy and kappa coefficient than the method using only Landsat-8 OLI 7 bands. In contrast, the classification method, which selected only NDBI as classification feature together with Landsat-8 OLI 7 bands did not show the improvement in classification accuracies.

• Journal of Biosystems Engineering
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• v.22 no.4
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• pp.433-438
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• 1997

The freshness of apple was evaluated by characterizing the surface texture of flesh cells. The freshness index which was related to the amount of wrinkles on the cell surface was defined to quantify the freshness. Four parameters relevant to the amount of the cell wrinkles were selected and measured using image analysis including wrinkle extraction procedure and Fast Fourier Transform of a wrinkle-extracted image. Out of 4 parameters, three parameters had highly significant correlations with the time elapsed after harvest. But it was concluded that two parameters out of such 3 parameters could be used for description of freshness index.

• Journal of Korean Biological Nursing Science
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• v.14 no.2
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• pp.77-83
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• 2012

Purpose: The purpose of this study was to identify the self image according to body mass index in middle school students. Methods: The study included 260 students. Self image was measured using structured questionnaires. Statistical analysis was performed using t-test, ANOVA, Scheffe's test and multiple regression analysis. Results: The proportions of under weight, normal weight, and overweight were 36.1%, 53.9%, 10.0% respectively. Also, the mean of the self image score was 4.0. The score of self image was significantly higher in the normal weight group than the over weight group or the under weight group. This trend was also consistent in multiple regression. The score of self image was lower in high school grades, low perceived record, under-weight and over-weight. Conclusion: This study shows that many students are under weight. The score of self image was related with body image. So, level of obesity in each student should also be considered, to elevate the self image.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.16-25
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• 2020

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5170-5188
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• 2015

This paper proposes a novel progressive secret image-hiding scheme based on the inpainting technique, the vector quantization technique (VQ) and the exploiting modification direction (EMD) technique. The proposed scheme first divides the secret image into non-overlapping blocks and categorizes the blocks into two groups: complex and smooth. The blocks in the complex group are compressed by VQ with PCA sorted codebook to obtain the VQ index table. Instead of embedding the original secret image, the proposed method progressively embeds the VQ index table into the cover images by using the EMD technique. After the receiver recovers the complex parts of the secret image by decoding the VQ index table from the shadow images, the smooth parts can be reconstructed by using the inpainting technique based on the content of the complex parts. The experimental results demonstrate that the proposed scheme not only has the advantage of progressive data hiding, which involves more shadow images joining to recover the secret image so as to produce a higher quality steganography image, but also can achieve high hiding capacity with acceptable recovered image quality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.6
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• pp.141-146
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• 2008

Recently, it is studying to provide to users through internet in the SensorWeb of OGC(Open Geospatial Consortium) saving and maintaining data and image information gathered from sensor network. It is necessary to study about data convergence as binding audio and video for delivering the sensing data and image information to users with real-time system. In this article, it suggests how to convergence sensing data and moving picture collected from the sensor network using index. This program indicates both of them that collected sensing data and information identified of moving picture in the integration index and based on this program provides sensing data moving picture at the same time referencing integration index, if the user asks. To verify suggested method designing real-time multimedia service structure using sensor network and image installation and implementing Ubiquitous realtime multimedia system integrating moving picture and sensing data based on index. As a result of this program, it is confirmed providing real-time multimedia service to request information of application service using integration index collected image and sensing data from wireless sensor network and image installation suggested data convergence method.

• Journal of Biosystems Engineering
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• v.31 no.6 s.119
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• pp.524-528
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• 2006

This study was performed to develop experimental model for milling degree and whiteness from analysis the CBB (colored bran balance) index using NMG dying and image processing. The endosperm layer increased and the pericarp, aleurone layer and CBB index decreased as the milling degree and whiteness increased. So, CBB index was closely linked to milling degree and whiteness. A empirical CBB index model was developed according to the milling degree and whiteness. The model were found to fit adequately to all test data with a coefficient of determination of 0.99, and therefore the CBB model proved to be quite applicable.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.04a
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• pp.328-331
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• 2000

In this paper , we propose a texture feature extraction method of reduce the massive computational time on extracting texture, features of large sized medical such as MRI, CT-scan , and an index structure, called GLTFT, to speed up the retrieval performance. For these, the original image is transformed into a compressed image by Wavelet transform , and textural features such as contrast, energy, entropy, and homogeneity of the compressed image is extracted by using GLCM(Gray Level Co-occurrence Metrix) . The proposed index structure is organized by using the textural features. The processing in compressed domain can give the solution of storage space and the reduction of computational time of feature extracting . And , by GLTFT index structure, image retrieval performance can be expected to be improved by reducing the retrieval range . Our experiment on 270 MRIs as image database shows that shows that such expectation can be got.

• Fashion & Textile Research Journal
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• v.15 no.6
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• pp.1010-1017
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• 2013

Current global textiles and fashion industries have gradually shifted focus to high value-added, high sensibility, and multi-functional products based on new human-friendliness and sustainable growth technologies. Textile design CAD systems have been developed in conjunction with computer hardware and software sector advances. This study compares the patterns or images of actual woven fabrics and virtual fabrics prepared with a textile design CAD system. In this study, several weave structures (such as fancy yarn weave and patterns) were prepared with a shuttle loom. The woven textile images were taken using a CCD camera. The same weave structure data and yarn data were fed into a textile design CAD system in order to simulate fabric images as similarly as possible. Similarity Index analysis methods allowed for an analysis of the index between the actual fabric specimen and the simulated image of the corresponding fabric. The results showed that repeated small pattern weaves provide superior similarity index values than those of a fancy yarn weave that indicate some irregularities due to fancy yarn attributes. A Complex Wavelet Structural Similarity(CW-SSIM) index resulted in a better index than other methods such as Multi-Scale(MS) SSIM, and Feature Similarity(FS) SSIM, across fabric specimen images. A correlation analysis of the similarity index based on an image analysis and a similarity evaluation by panel members was also implemented.

• Journal of Biomedical Engineering Research
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• v.21 no.3 s.61
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• pp.233-237
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• 2000

In general. fiber-optic medical endoscopes are made from glass step index (SI) fibers. These endoscopes have limitations in both image quality and mechanical properties. In particular. the image resolution of the SI endoscopes is limited to about 5$\mu$m. In this study the image resolution of plastic graded index (GRIN) super-resolution image guides with pixel sizes from 7 to 2.5 $\mu$m were measured and compared with those of 91ass SI image guides. There is an improvement in resolution of the plastic GRIN image guides as the microfiber diameter is reduced from 7 $\mu$m to 2.5 $\mu$m. The measured resolution of plastic GRIN image guide with 2.5 $\mu$m microfibers is more than a factor of two higher than that of g1ass SI image guide with 5$\mu$m microfibers. This new design of optical systems could have a major impact on a wide array of future optical systems used in defense. industrial, and medical applications.