• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.2
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• pp.387-396
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• 1999

In dentistry. RadioVisioGraphy was introduced as a first electronic dental x-ray imaging modality in 1989. Thereafter. many types of direct digital radiographic system have been produced in the last decade. They are based either on charge-coupled device(CCD) or on storage phosphor technology. In addition. new types of digital radiographic system using amorphous selenium. image intensifier etc. are under development. Advantages of digital radiographic system are elimination of chemical processing, reduction in radiation dose. image processing, computer storage. electronic transfer of images and so on. Image processing includes image enhancement. image reconstruction. digital subtraction, etc. Especially digital subtraction and reconstruction can be applied in many aspects of clinical practice and research. Electronic transfer of images enables filmless dental hospital and teleradiology/teledentistry system. Since the first image management and communications system(IMACS) for dentomaxillofacial radiology was reported in 1992. IMACS in dental hospital has been increasing. Meanwhile. researches about computer-assisted diagnosis, such as structural analysis of bone trabecular patterns of mandible. feature extraction, automated identification of normal landmarks on cephalometric radiograph and automated image analysis for caries or periodontitis. have been performed actively in the last decade. Further developments in digital radiographic imaging modalities. image transmission system. imaging processing and automated analysis software will change the traditional clinical dental practice in the 21st century.

• Computers and Concrete
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• v.14 no.3
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• pp.315-325
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• 2014

Concrete is an important material in most of civil constructions. Many properties of concrete can be determined through analysis of concrete images. Image segmentation is the first step for the most of these analyses. An automated system for segmentation of concrete images into microstructures using texture analysis is proposed. The performance of five different classifiers has been evaluated and the results show that using an Artificial Neural Network classifier is the best choice for an automatic image segmentation of concrete.

• Journal of Animal Environmental Science
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• v.6 no.1
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• pp.23-30
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• 2000

A automated noncontact weight system for pigs consisted of a CCD-type video camera and 10 photo sensors connected to a computer. In the experiment 20 pigs(Large Yorkshire $\times$ Landrace breed) weighing from 95kg to 115kg were used. Pig's original image data was transformed to a binary image an image excluding head and tail portion from the whole binary image and the area of pig was calculated. Then pig's volume was calculated by multiplying the area by the body hight measured with photo sensors. The correlation equation between the above volume(x) and pig's weight was y=0.0007 x -9.2152($R^2$=0.9965) Performance of a automated noncontact weighing system for pigs was tested with this equation. The results showed $\pm$0.65kg average error and 1.63kg maximum error. It was concluded that performance of a automated noncontact weighing system is excellent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.225-232
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• 2010

In this study, an automated ultrasonic testing system and post signal and image processing techniques are developed in order to construct ultrasonic flaw images in weldments. Image processing algorithms are built into the flaw image processing system for the automated ultrasonic testing system. The developed signal and image analysis algorithms addressed in this study include an A-Scan data compression algorithm, ultrasonic image amplification algorithm and B-scan flaw image correction algorithm(SAFT). This flaw image processing system for the automated ultrasonic testing system can be applied to various inspection fields.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.696-701
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• 2002

This paper describes some results of change detection in Tokyo metropolitan area, Japan , using the Landsat TM data, and methods to quantify the ground cover classes. The changes are analyzed using the measures of not only conventional spectral classes but also a set of landscape indices to describe spatial properties of ground cove types using fractal dimension of objects, entropy in the specific windows defining the neighbors of focusing locations. In order eliminate the seasonal radiometric effects on TM data, an automated class labeling method is also attempted. Urban areas are also delineated automatically by defining the boundaries of the urban area. These procedures for urban change detection were implemented by the unified image computing methods proposed by the author, they can be automated in coherent and systematic ways, and it is anticipated to automate the whole procedures. The results of this analysis suggest that Tokyo metropolitan area was extended to the suburban areas along the new transportation networks and the high density area of Tokyo were also very much extended during the period between 1985 and 1995.

• Toxicological Research
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• v.18 no.4
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• pp.369-374
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• 2002

The present study was performed to validate an automated image analysis system (Loats Automated Micronucleus Scoring System) for the mouse bone marrow micronucleus assay, comparing with conventional microscopic scoring. Two studies were conducted to provide slides for a comparison of micro-nucleated polychromatic erythrocytes (MNPCEs) values collected manually to those collected by the auto-mated system. Test article A was used as an example of a compound negative for the induction of micronuclei and test article B was wed as a micronucleus-inducing agent to elicit a positive response. Cyclophosphamide was included to provide an positive control in two studies. Bone marrow samples were collected 24 h after administration of test article A and B in male ICR mice. The cells were fixed with absolute methanol and stained with May-Grunwald and Giemsa. The number of MNPCEs was determined by the analysis of 1000 total PCEs per bone marrow sample. In addition to micronucleus scoring, an index of bone marrow toxicity based on PCE ratio (% of PCEs to total erythrocytes) was determined for each sample. The automated and manual scoring was similar when the MNPCEs incidence induced by each test article was less than 10. However manual scoring was able to effectively enumerate micronucleated PCEs in mouse bone marrow when MNPCEs incidence was more than 10, such as cyclophosphamide treatment. Conversely, PCE ratio was superior in computer-assisted image analysis. Taken together, it is suggested that improvement of the automated image analysis may be necessary to render the automatic scoring as sensitive as manual scoring for routine counting of micronuclei, especially because it is superior in objectivity and high throughput scoring.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.4
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• pp.195-204
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• 2014

This paper presents the depth evaluation for object detection by automated assembling robots. Pattern distortion analysis from a structured light system identifies an object with the greatest depth from its background. An automated assembling robot should prior select and pick an object with the greatest depth to reduce the physical harm during the picking action of the robot arm. Object detection is then combined with a depth evaluation to provide contour, showing the edges of an object with the greatest depth. The contour provides shape information to an automated assembling robot, which equips the laser based proxy sensor, for picking up and placing an object in the intended place. The depth evaluation process using structured light for an automated electronics assembling robot is accelerated for an image frame to be used for computation using the simplest experimental set, which consists of a single camera and projector. The experiments for the depth evaluation process required 31 ms to 32 ms, which were optimized for the robot vision system that equips a 30-frames-per-second camera.

• Journal of the Korean Society of Visualization
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• v.13 no.3
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• pp.15-19
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• 2015

We developed a high-throughput microscopy (HTM) method which enabled us to replace a conventional phase contrast microscopy (PCM) method that has been used as a standard analytical method for airborne asbestos. We could obtain the concentration of airborne asbestos fibers under detection limit by automated image processing and analysis using HTM method. Here we propose an improved image processing algorithm with variable parameters to enhance the accuracy of the HTM analysis. Since the variable parameters that compensate the difference of the brightness are applied to the individual images in our new image processing method, it is possible to enhance the accuracy of the automatic image analysis method for sample slides with low asbestos concentration that caused errors in binary image processing. We demonstrated that enumeration of fibers by improved image processing algorithm remarkably enhanced the accuracy of HTM analysis in comparison with PCM. The improved HTM method can be a potential alternative to conventional PCM.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• Korean Journal of Geomatics
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• v.1 no.1
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• pp.85-93
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• 2001

Geospatial database, which is the basis for Geo-Spatial Information Systems, is produced by conventional mapping methods. Recently, with increased demand for digital forms of the geospatial database, studies are carried out to automate its production. The automated mapping system is composed of the image acquisition subsystem, positioning subsystem, point referencing subsystem and the visualization subsystem. The image acquisition subsystem is the most important part of the overall production line because it is the starting point and will affect all subsequent processes. This paper presents a software analysis and design of the image acquisition subsystem. The design was carried out using the Unified Modeling Language which is a modeling method used extensively in the software engineering field.