• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.186-192
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• 2019

In general, many marine organisms are attached to the bottom of a ship in operation or a ship in construction. Due to this phenomenon, the roughness of the ship surface increases, resulting in loss of ship speed, resulting in economic losses and environmental pollution. This study acquires / utilizes camera images attached to ship's bottom and underwater drones to check the condition of bottom. The acquired image will determine the roughness according to marine life by the administrator's visual confirmation. Therefore, by applying a filter algorithm to correct the image to the original image can help in the correct determination of whether or not attached to marine life. Various correction filters are required for the underwater image correction algorithm, and the lighting suitable for the dark underwater environment has a great influence on the judgment. The results of the research test according to the calibration algorithm and the roughness of each algorithm are considered to be applicable to many fields.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.55-63
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• 2013

Purpose: The present study aimed at image processing methods for automatic cell pattern recognition and morphological analysis for tissue engineering applications. The primary aim was to ascertain the novel algorithm of adaptive brightness correction from microscopic images for use as a potential image analysis. Methods: General microscopic image of cells has a minor problem which the central area is brighter than edge-area because of the light source. This may affect serious problems to threshold process for cell-number counting or cell pattern recognition. In order to compensate the problem, we processed to find the central point of brightness and give less weight-value as the distance to centroid. Results: The results presented that microscopic images through the brightness correction were performed clearer than those without brightness compensation. And the classification of mixed cells was performed as well, which is expected to be completed with pattern recognition later. Beside each detection ratio of hBMSCs and HeLa cells was 95% and 92%, respectively. Conclusions: Using this novel algorithm of adaptive brightness correction could control the easier approach to cell pattern recognition and counting cell numbers.

• Korean Journal of Radiology
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• v.20 no.1
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• pp.94-101
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• 2019

Objective: To investigate the efficacy of motion-correction algorithm (MCA) in improving coronary artery image quality and measurement accuracy using an anthropomorphic dynamic heart phantom and 256-detector row computed tomography (CT) scanner. Materials and Methods: An anthropomorphic dynamic heart phantom was scanned under a static condition and under heart rate (HR) simulation of 50-120 beats per minute (bpm), and the obtained images were reconstructed using conventional algorithm (CA) and MCA. We compared the subjective image quality of coronary arteries using a four-point scale (1, excellent; 2, good; 3, fair; 4, poor) and measurement accuracy using measurement errors of the minimal luminal diameter (MLD) and minimal luminal area (MLA). Results: Compared with CA, MCA significantly improved the subjective image quality at HRs of 110 bpm (1.3 ± 0.3 vs. 1.9 ± 0.8, p = 0.003) and 120 bpm (1.7 ± 0.7 vs. 2.3 ± 0.6, p = 0.006). The measurement error of MLD significantly decreased on using MCA at 110 bpm (11.7 ± 5.9% vs. 18.4 ± 9.4%, p = 0.013) and 120 bpm (10.0 ± 7.3% vs. 25.0 ± 16.5%, p = 0.013). The measurement error of the MLA was also reduced using MCA at 110 bpm (19.2 ± 28.1% vs. 26.4 ± 21.6%, p = 0.028) and 120 bpm (17.9 ± 17.7% vs. 34.8 ± 19.6%, p = 0.018). Conclusion: Motion-correction algorithm can improve the coronary artery image quality and measurement accuracy at a high HR using an anthropomorphic dynamic heart phantom and 256-detector row CT scanner.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.299-301
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• 1996

Since a standard lens has small sight angle, a fish-eye lens can be used in order to obtain wide sight angle for the robot vision system. In spite of the advantage, the image through the lens has variable resolution; the central information of the lens is of high resolution, but the peripheral information is of low resolution. Owing to this difference of resolution, the variable resolution image should be transformed to a uniform resolution image in order to determine the positions of the objects in the image. In this work, the correction method for the distorted image is presented and the performance is analyzed. Furthermore, the camera with a fish eye lens can be used to determine the real world coordinates. The performance is shown through experiments.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.181-190
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• 2013

We propose an interpolation method considering barrel distortion of fisheye lens using nearest pixels on a corrected image. The correction of barrel distortion comprises coordinate transformation and interpolation. This paper focuses on interpolation. The proposed interpolation method uses nearest four coordinates on a corrected image rather than on a distorted image unlike existing techniques. Experimental results show that both subjective and objective image qualities are improved.

• Journal of the HCI Society of Korea
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• v.6 no.1
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• pp.21-26
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• 2011

This paper presents a robust method for facial image synthesis under varying illumination by combining illumination correction and Poisson image processing techniques. The presented method automatically detects skin area and corrects highly saturated regions that can cause bad effects on the final synthesis image. The developed method can be applied to various facial synthesis applications by correcting illumination variations that can occur frequently on photos taken with a camera phone.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.224-227
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• 1999

This paper presents a design of the real-time preprocessor for CMOS image sensor suitable to the digital camera applications. CMOS image sensor offers some advantages in on-chip integration, system power reduction, and low cost. However, it has a lower-quality image than CCDs. We describe an image enhancement algorithm, which includes color interpolation, color correction, gamma correction, sharpening, and automatic exposure control, to compensate for this disadvantage, and present its efficient hardware architecture to implement on the real-time processor. The presented real-time preprocessor was designed using VHDL, and it contains about 19.2K logic gates. We also implement our system on FPGA chips in order to provide the real-time adjustment and it was successfully tested.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.211-214
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• 2007

With the recent development of spatial information technology, the relative importance of satellite image contents has increased to about 62%, the techniques related to satellite images have improved, and their demand is gradually increasing. Accordingly, a standard processing method for the whole process of collection from satellites to distribution of satellite images is required in many countries for efficient distribution of images and improvement of their utilization. This study presents the processor standardization technique for the preprocessing of satellite images including geometric correction, orthorectification, color adjustment, interpolation for DEM (Digital Elevation Model) production, rearrangement, and image data management, which will standardize the subjective, complex process and improve their utilization by making it easy for general users to use them

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.111-117
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• 2006

This paper describes the design principles and methods of electronic processor for thermal imager with 320$\times$240 staring array infrared detector. For the detector's nonuniformity correction and excellent image quality, we have designed the multi-point correction method using the defocusing technique of the optics. And to enhance the image of low contrast and improve the detection capability, the new technique of histogram processing has been designed. Through these image processing techniques, we have developed the high quality thermal imager and acquired a satisfactory thermal image. The result of MRTD(Minimum Resolvable Temperature Difference) is $0.1^{\circ}C$ at 4cycles/mard.

• Progress in Medical Physics
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• v.11 no.1
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• pp.39-47
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• 2000

In Stereotactic Radiosurgery (SRS), there are three imaging methods of target localization, such as digital subtraction Angiography (DSA), computed tomography (CT), magnetic resonance imaging (MRI). Especially, DSA and MR images have a distortion effect generated by each modality. In this research, image properties of DSA were studied. A first essential condition in SRS is an accurate information of target locations, since high dose used to treat a patient may give a complication on critical organ and normal tissue. Hut previous localization program did not consider distortion effect which was caused by image intensifier (II) of DSA. A neurosurgeon could not have an accurate information of target locations to operate a patient. In this research, through distortion correction, we tried to calculate accurate target locations. We made a grid phantom to correct distortion, and a target phantom to evaluate localization algorithm. The grid phantom was set on the front of II, and DSA images were obtained. Distortion correction methods consist of two parts: 1. Bilinear transform for geometrical correction and bilinear interpolation for gray level correction. 2. Automatic detection method for calculating locations of grid crosses, fiducial markers, and target balls. Distortion was corrected by applying bilinear transform and bilinear interpolation to anterior-posterior and left-right image, and locations of target and fiducial markers were calculated by the program developed in this study. Localization errors were estimated by comparing target locations calculated in DSA images with absolute locations of target phantom. In the result, the error in average with and without distortion correction is $\pm$0.34 mm and $\pm$0.41 mm respectively. In conclusion, it could be verified that our localization algorithm has an improved accuracy and acceptability to patient treatment.