• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.55-65
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• 2019

Although crack on concrete exists from its early formation, crack requires attention as it affects stiffness of structure and can lead demolition of structure as it grows. Detecting cracks on concrete is needed to take action prior to performance degradation of structure, and deep learning can be utilized for it. In this study, transfer learning, one of the deep learning techniques, was used to detect the crack, as the amount of crack's image data was limited. Pre-trained Inception-v3 was applied as a base model for the transfer learning. Web scrapping was utilized to fetch images of concrete wall with or without crack from web. In the recognition of crack, image post-process including changing size or removing color were applied. In the visualization of crack, source images divided into 30px, 50px or 100px size were used as input data, and different numbers of input data per category were applied for each case. With the results of visualized crack image, false positive and false negative errors were examined. Highest accuracy for the recognizing crack was achieved when the source images were adjusted into 224px size under gray-scale. In visualization, the result using 50 data per category under 100px interval size showed the smallest error. With regard to the false positive error, the best result was obtained using 400 data per category, and regarding to the false negative error, the case using 50 data per category showed the best result.

• Journal of Conservation Science
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• v.37 no.3
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• pp.220-231
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• 2021

The use of digital copies of film-based analog images and the introduction of digital radiographic imaging systems using image plates gradually replace the non-destructive radiationirradiation method of Cultural Heritage. The quality of images obtained from this technique is affected by conditions such as tube voltage, tube current, and exposure time, type of image acquisition medium, distance of the artifacts from the image acquisition medium, and thickness of artifacts. In this study, we evaluated the grayscale image obtained using GE's Computed Radiograhpy (CR) imaging system, the transmission characteristics of the X-ray source for each tree type (pine, chestnut, sawtooth oak, ginkgo) used in wooden Cultural Heritage, and the signal-to-noise ratio (SNR) and contrast. The GE's CR imaging were analyzed using the Duplex wire image quality indicator, line-pair gauges.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.99-112
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• 2019

Cracks on pavement surfaces are critical signs and symptoms of the degradation of pavement structures. Image-based pavement crack detection is a challenging problem due to the intensity inhomogeneity, topology complexity, low contrast, and noisy texture background. In this paper, we address the problem of pavement crack detection and segmentation at pixel-level based on a Deep Neural Network (DNN) using gray-scale images. We propose a novel DNN architecture which contains a modified U-net network and a high-level features network. An important contribution of this work is the combination of these networks afforded through the fusion layer. To the best of our knowledge, this is the first paper introducing this combination for pavement crack segmentation and detection problem. The system performance of crack detection and segmentation is enhanced dramatically by using our novel architecture. We thoroughly implement and evaluate our proposed system on two open data sets: the Crack Forest Dataset (CFD) and the AigleRN dataset. Experimental results demonstrate that our system outperforms eight state-of-the-art methods on the same data sets.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.390-398
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• 2022

Ultrasound examination using ultrasound equipment is an ultrasound device that images human organs using sound waves and is used in various areas such as diagnosis, follow-up, and treatment of diseases. However, if the quality of ultrasound equipment is not guaranteed, the possibility of misdiagnosis increases, and the diagnosis rate decreases. Accordingly, The Korean Society of Radiology and Korea society of Ultrasound in Medicine presented guidelines for quality management of ultrasound equipment using ATS-539 phantom. The DenseNet201 classification algorithm shows 99.25% accuracy and 5.17% loss in the Dead Zone, 97.52% loss in Axial/Lateral Resolution, 96.98% accuracy and 20.64% loss in Sensitivity, 93.44% accuracy and 22.07% loss in the Gray scale and Dynamic Range. As a result, it is the best and is judged to be an algorithm that can be used for quantitative evaluation. Through this study, it can be seen that if quantitative evaluation using artificial intelligence is conducted in the qualitative evaluation item of ultrasonic equipment, the reliability of ultrasonic equipment can be increased with high accuracy.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.21-28
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• 2009

Color polarity classification is a process to determine whether the color of text is bright or dark and it is prerequisite task for text extraction. In this paper we propose a color polarity method to extract text region. Based on the observation for the text and background regions, the proposed method uses the ratios of sizes and standard deviations of bright and dark regions. At first, we employ Otsu's method for binarization for gray scale input region. The two largest segments among the bright and the dark regions are selected and the ratio of their sizes is defined as the first measure for color polarity classification. Again, we select the segments that have the smallest standard deviation of the distance from the center among two groups of regions and evaluate the ratio of their standard deviation as the second measure. We use these two ratio features to determine the text color polarity. The proposed method robustly classify color polarity of the text. which has shown by experimental result for the various font and size.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.45-54
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• 2009

In this paper, we propose an adult images detection algorithm using a mean intensity filter and an improved 2D Hough Transform. This paper is composed of three major steps including a training step, a recognition step, and a verification step. The training step generates a mean nipple variance filter that will be used for detecting nipple candidate regions in the recognition step. To make the mean variance filter, we converts an input color image into a gray scale image and normalize it, and make an average intensity filter for nipple areas. The recognition step first extracts edge images and finds connected components, and decides nipple candidate regions by considering the ratio of width and height of a connected component. It then decides final nipple candidates by calculating the similarity between the learned nipple average intensity filter and the nipple candidate areas. Also, it detects breast lines of an input image through the improved 2D Hough transform. The verification step detects breast areas and identifies adult images by considering the relations between nipple candidate regions and locations of breast lines.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.127-133
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• 2011

Characters in natural image are an important information with various context. Previous work of character region detection algorithms is not detect of character region in case of image complexity and the surrounding lighting, similar background to character, so this paper propose an method of character region detection in natural image using edge and connected component by morphological reconstructions. Firstly, we detect edge using Canny-edge detector and connected component with local min/max value by morphological reconstructed-operation in gray-scale image, and labeling each of detected connected component elements. lastly, detected candidate of text regions was merged for generation for one candidate text region, Final text region detected by checking the similarity and adjacency of neighbor of text candidate individual character. As the results of experiments, proposed algorithm improved the correctness of character regions detection using edge and connected components.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.103-109
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• 2016

Polyethylene pipes has useful benefits which are anti-corrosive and flexible material, so it is used to gas pipes but also class 3 water pipes of nuclear power plant, process pipes of petrochemical plant and chemical plant. So the usage of polyethylene pipes is widely increased. But it has been limited for the usage of polyethylene, because it can not be directly detected to fusion joints by using non destructive evaluation. Polyethylene pipes are connected by two methods, one is butt fusion and the other is electrofusion. Butt fusion is widely used to connecting the pipes. It is proposed to method for determining the reliability of joints in this study that is detection of the melt flow zone at fusion joints. In this study, middle density polyethylene is used, outside diameter of the test specimen is 225mm and thickness is 20.5mm. Speed of ultrasonic of this test specimen is 2,200m/s. Test specimens were fabricated by varying the heating time which means from 0% to 130% applying time through heating plate to polyethylene for detecting melt flow zone. Also 4 additional test specimens were made, one was made that not scrapping attached surface of pipes but applying 100% of the proper heating time and the others were made to include of soil, gravel and vinly tape paper at fusion joints, that were also applied 100% of proper heating time. Ultrasonic testing to measure the melt flow zone of 20 test specimens was conducted by using 3.5MHz and 5.0MHz ultrasonic probes and melt flow zone measuring was conducted to three times at different point to one specimen. To differentiate the melt flow zone signal, post image processing was equally conducted to all test results and image levels, contrast, sharpen, threshold were adopted to all teat results and the test results were displayed gray scale. From the results, for the shorter heating times the reflection area of multiple echo have been increased, so the data was obtained from the position where it can be eliminated as much as possible. At 80% of proper heating time(168 sec.), the signal of melt flow zone was obtained clearly, so measuring could be conducted. From 7% of proper heating time(15 sec.) to shorter heating times. we could not obtain the signal because test specimen was not fused. From the result, we can verify that measuring of melt flow zone by using phased array ultrasonic imaging method is possible. And we can verify to complete and incomplete butt fusion by measuring the melt flow zone.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.35-39
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• 2009

Purpose: Diagnostic and functional imaging softwares in Nuclear Medicine have been developed significantly. But, there are some limitations which like take a lot of time. In this article, we introduced that the basic concept of macro to help understanding macro and its application to Brain SPECT processing. We adopted macro software to SPM processing and PACS verify processing of Brain SPECT processing. Materials and Methods: In Brain SPECT, we choose SPM processing and two PACS works which have large portion of a work. SPM is the software package to analyze neuroimaging data. And purpose of SPM is quantitative analysis between groups. Results are made by complicated process such as realignment, normalization, smoothing and mapping. We made this process to be more simple by using macro program. After sending image to PACS, we directly input coordinates of mouse using simple macro program for processes of color mapping, adjustment of gray scale, copy, cut and match. So we compared time for making result by hand with making result by macro program. Finally, we got results by applying times to number of studies in 2007. Results: In 2007, the number of SPM studies were 115 and the number of PACS studies were 834 according to Diamox study. It was taken 10 to 15 minutes for SPM work by hand according to expertness and 5 minutes and a half was uniformly needed using Macro. After applying needed time to the number of studies, we calculated an average time per a year. When using SPM work by hand according to expertness, 1150 to 1725 minutes (19 to 29 hours) were needed and 632 seconds (11 hours) were needed for using Macro. When using PACS work by hand, 2 to 3 minutes were needed and for using Macro, 45 seconds were needed. After applying theses time to the number of studies, when working by hand, 1668 to 2502 minutes (28 to 42 hours) were needed and for using Macro, 625 minutes (10 hours) were needed. Following by these results, it was shown that 1043 to 1877 (17 to 31 hours were saved. Therefore, we could save 45 to 63% for SPM, 62 to 75% for PACS work and 55 to 70% for total brain SPECT processing in 2007. Conclusions: On the basis of the number of studies, there was significant time saved when we applied Macro to brain SPECT processing and also it was shown that even though work is taken a little time, there is a possibility to save lots of time according to the number of studies. It gives time on technologist's side which makes radiological technologist more concentrate for patients and reduce probability of mistake. Appling Macro to brain SPECT processing helps for both of radiological technologists and patients and contribute to improve quality of hospital service.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.463-472
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• 2021

Demand for examinations using transvaginal transducer with high frequencies is increasing to observe pelvic organs in gynecological ultrasound tests. However, the quality control of the replacement probe in clinical trials is not properly implemented and the evaluation criteria have not been established. Therefore, 58 transvaginal transducers and 20 convex transducers were applied to the ATS-539 ultrasound phantom for 20 ultrasound devices currently in clinical use to obtain their respective images and measure them quantitatively and qualitatively. For quantitative measurements, vertical measurement, horizontal measurement, and focal zone and qualitative measurements, dead zone, axial·lateral resolution, sensitivity, functional resolution, gray scale·dynamic range were performed. Quantitative statistical analysis showed significant differences between the two transducers in the lateral measurement and local area (p<0.05). qualitative comparative analysis showed differences in sensitivity and functional resolution. This occurs due to the difference in frequency between transducers and the transducer's injection geometry. Based on the above experiments, the tolerance for horizontal measurement is raised to 10% (±8 mm), the tolerance for sensitivity is observed up to 6 cm deep, which is 12 cm deep,which is the level of the third quartile (75%). The permissible range of functional resolution is up to 6 (12 cm), 6 (12 cm), 11 (11 cm), 9 (9 cm), 6 (6 cm) target, which is the level of the third quartile (75%). It is considered reasonable to adjust the depth of targets in gray scale·dynamic range to measure at a depth of 2 cm, which is 50% of the depth of 4 cm. As above, the criteria for evaluating the quality of transvaginal transducer for use in the past have been proposed and it is expected that this study will be used as a basic data for the production of phantom exclusively for transvaginal transducer in the future.