• KIPS Transactions on Software and Data Engineering
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• v.11 no.2
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• pp.87-92
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• 2022

Image-based application testing proposes an application testing method via image structure comparison. This test method allows testing on various devices without relying on various types of device operating systems or GUI. Traditional studies required the creation of a tester for each variant in the existing case, because it differs from the correct image for operating system changes, screen animation execution, and resolution changes. The study determined that the screen is the same for variations. The tester compares the underlying structure of the objects in the two images and extracts the regions in which the differences exist in the images, and compares image similarity as characteristic points of the Faster D2-Net. The development of the Faster D2-Net reduced the number of operations and spatial losses compared to the D2-Net, making it suitable for extracting features from application images and reducing test performance time.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.389-392
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• 2000

In this paper, we propose a novel post processing method of deconvolution for SAR images based on phase extension inverse filtering, which improves spatial resolution as well as effectively eliminates sidelobes with low computational complexity. It extends the bandwidth only to control the magnitude of the processed SAR data without distortions of the phase in frequency domain unlike the other techniques such as spatially variant apodization (SVA), and other deconvolution techniques. We compare the image processed by the proposed method with images processed by uniform weighting function, Hamming weighting function whose coefficient is 0.75, and SVA.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.3
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• pp.225-244
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• 2014

In this work, we discuss segmentation algorithms based on the level set method that incorporates shape prior knowledge. Fundamental segmentation models fail to segment desirable objects from a background when the objects are occluded by others or missing parts of their whole. To overcome these difficulties, we incorporate shape prior knowledge into a new segmentation energy that, uses global and local image information to construct the energy functional. This method improves upon other methods found in the literature and segments images with intensity inhomogeneity, even when images have missing or misleading information due to occlusions, noise, or low-contrast. We consider the case when the shape prior is placed exactly at the locations of the desired objects and the case when the shape prior is placed at arbitrary locations. We test our methods on various images and compare them to other existing methods. Experimental results show that our methods are not only accurate and computationally efficient, but faster than existing methods as well.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.12
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• pp.1039-1047
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• 2015

Contact type sensors (e.g., displacement sensor and strain gauge) were typically used to evaluate the safety and mechanical properties in machines and construction. However, those contact type sensors have been constrained because of measurement problems such as surface roughness, temperature, humidity, and shape. The Digital Image Correlation (DIC) measurement system is a vision measurement system. This measurement system uses the taken image using a CCD camera and calculates the image correlation between the reference image and the deformed image under external force to measure the displacement and strain rates. In this paper, we discuss methods to improve the measurement precision of the digital image correlation measurement system. A tensile test was conducted to compare the precision improvement effects, by using the universal test machine and the DIC measurement system, with the use of subpixel algorithms, i.e., the Coarse Fine Search (CFS) algorithm and the Peak Finding (PF) algorithm.

• Journal of Korean Academy of Nursing Administration
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• v.15 no.4
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• pp.610-616
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• 2009

Purpose: The purpose of this study was to compare and analyze the nurses' image perceived by nursing and health allied college students in Korea. Method: The data was collected from October 15th to November 15th, 2004. Subjects were composed of 679 students in three-year Junior College. The data was analyzed by SPSS 12.0 PC+ Win. The difference of nurse' image among departments and locations of Junior College were analyzed by t-test, ANOVA and Tukey test. Result: The mean score of nurses' image 3.1 point of the total 5 point. Nurses' image is showed significantly difference according to the departments; the department of nursing (3.54), physical therapy (3.01), radiology (2.97), emergency medical technology (2.76) and clinical pathology (2.67). Nurses' image was significantly differed among the 4 domains according to 5 departments; 'the qualification of nurse', 'the role of nurse', 'the interpersonal relationship of nurse', 'the social participation of nurse'. Nurses' image formed through directly contacting with nurses' and seeing nurses' action (69.1%), watching nurse in TV drama (15.9%). Conclusion: It is considered that nursing and health allied college students were affected by inter-communications with nurses' more than by mass media.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.173-178
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• 2014

In this study, the new color image processing algorithms with an android-based mobile device are developed to detect the abnormal color densities in a skin image and interpret them as the vitiligo lesions. Our proposed method is firstly based on transforming RGB data into HSI domain and segmenting the imag into the vitiligo-skin candidates by applying Otsu's threshold algorithm. The structure elements for morphological image processing are suggested to delete the spurious regions in vitiligo regions and the image blob labeling algorithm is applied to compare RGB color densities of the abnormal skin region with them of a region of interest. Our suggested color image processing algorithms are implemented with an android-platform smartphone and thus a mobile device can be utilized to diagnose or monitor the patient's skin conditions under the environments of pervasive healthcare services.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.239-251
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• 2016

Hyperspectral image is widely used for land cover classification because it has a number of narrow bands and allow each pixel to include much more information in comparison with previous multi-spectral image. However, Higher spectral resolution of hyperspectral image results in an increase in data volumes and a decrease in noise efficiency. SAM(Spectral Angle Mapping), a method based on vector inner product to compare spectrum distribution, is a highly valuable and popular way to analyze continuous spectrum of hyperspectral image. SAM is shown to be less accurate when it is used to analyze hyperspectral image for land cover classification using spectral library. this inaccuracy is due to the effects of atmosphere. We suggest a decision tree based method to compensate the defect and show that the method improved accuracy of land cover classification.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.423-431
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• 2009

There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.

• Journal of the Korean Society of Physical Medicine
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• v.7 no.4
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• pp.533-539
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• 2012

PURPOSE: The purpose of this study was to investigate the effect of pelvic floor muscle contraction with image feedback on Abdominal muscle thickness. METHODS: Twenty three adults participated in this study. Abdominal muscle thickness was measured by ultrasound in three condition(rest, pelvic floor muscle contraction, pelvic floor muscle contraction with image feedback). Subjects was contraction pelvic floor muscle by general method. And ultrasound(convex probe, 3.5MHz) was used to image feedback for selective pelvic floor muscle contraction. One-way ANOVA was used to compare abdominal muscle thickness in three condition. RESULTS: There was no significant difference in external oblique(p=.514) and internal oblique muscle(p=.250) thickness by three condition. There was significant difference in transverse abdominis thickness by three condition (Transverse abdominis thickness was highest while Pelvic floor muscle contraction than pelvic floor muscle contraction with image feedback and rest.)(p=.000). CONCLUSION: This study shows that pelvic floor muscle contraction with image feedback increase the thickness of transverse abdominis lesser than general pelvic floor muscle contraction.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.12 no.1
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• pp.15-20
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• 2005

Purpose: This study was done to compare of adult body composition and body image before and after regular exercise program at a sports center. Method: The participants were 32 adults who were beginning regular exercise at a sports center in D city. The body composition was measured by body weight, soft lean mass, fat mass, percent body fat, fat distribution, degree of obesity and BMI, using the Inbody 3.0. Body image. Data were collected using structured questionnaires and analyzed using paired t-test. Results: 1. Significant improvement was shown in body composition. 2. The score for body image increased after the program, but the change was not statistically significant. Conclusion: The short-term exercise program was very effective in improving body composition, but changes in the evaluation of body image need long-term exercise. Also, we were concluded that it is very important to consider preference level when evaluating body composition and body image.