• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.221-228
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• 2024

As the importance of cardiovascular health is highlighted, research on its correlation with blood pressure, the most important indicator, is being actively conducted. Therefore, extensive clinical data is essential, but the measurement of the central arterial blood pressure waveform must be performed invasively within the artery, so the quantity and quality are limited. This study suggested a mock circulatory robot and artificial aorta to reproduce the blood pressure waveform generated by the overlap of forward and reflected waves. The artificial aorta was fabricated with biomimetic silicone to mimic the physiological structure and vascular stiffness of the human. A pressurizing chamber was implemented to prevent distortion of the blood pressure waveform due to the strain-softening of biomimetic silicone. The reproduced central arterial blood pressure waveforms have similar magnitude, shape, and propagation characteristics to humans. In addition, changes in blood pressure waveform due to aging were also reproduced by replacing an artificial aorta with various stiffness. It can be expanded to construct a biosignal database and health sensor testing platform, a core technology for cardiovascular health-related research.

• Journal of IKEEE
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• v.22 no.4
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• pp.1214-1217
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• 2018

In this paper, we propose the development of a Small $360^{\circ}$ Oral Scanner embedded board. The proposed small $360^{\circ}$ oral scanner embedded board consists of image level and transfer method changing part FPGA part, memory part and FIFO to USB transfer part. The image level and transmission mode change unit divides the MIPI format oral image received through the small $360^{\circ}$ oral cavity image sensor and the image sensor into low power signal mode and high speed signal mode and distributes them to the port and transfers the level shift to the FPGA unit. The FPGA unit performs functions such as $360^{\circ}$ image distortion correction, image correction, image processing, and image compression. In the FIFO to USB transfer section, the RAW data transferred through the FIFO in the FPGA is transferred to the PC using USB 3.0, USB 3.1, etc. using the transceiver chip. In order to evaluate the efficiency of the proposed small $360^{\circ}$ oral scanner embedded board, it has been tested by an authorized testing institute. As a result, the frame rate per second is over 60 fps and the data transfer rate is 4.99 Gb/second

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.28-36
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• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.1-9
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• 2024

This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.81-86
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• 2024

The Image Signal Processor (ISP) converts RAW images captured by the camera sensor into user-preferred sRGB images. While RAW images contain more meaningful information for image processing than sRGB images, RAW images are rarely shared due to their large sizes. Moreover, the actual ISP process of a camera is not disclosed, making it difficult to model the inverse process. Consequently, research on learning the conversion between sRGB and RAW has been conducted. Recently, the ParamISP[1] model, which directly incorporates camera parameters (exposure time, sensitivity, aperture size, and focal length) to mimic the operations of a real camera ISP, has been proposed by advancing the simple network structures. However, existing studies, including ParamISP[1], have limitations in modeling the camera ISP as they do not consider the degradation caused by lens shading, optical aberration, and lens distortion, which limits the restoration performance. This study introduces Positional Encoding to enable the camera ISP neural network to better handle degradations caused by lens. The proposed positional encoding method is suitable for camera ISP neural networks that learn by dividing the image into patches. By reflecting the spatial context of the image, it allows for more precise image restoration compared to existing models.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.599-606
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• 2015

International Hydrographic Organization(IHO) adopted standard S-100 as the international standard Geographic Information System(GIS) that can be generally used in the maritime sector. Accordingly, the next-generation system to support navigation information based on GIS standard technology has being developed. AR based navigation information system that supported navigation by overlapping navigation information on the CCTV image has currently being developed. In this study, we considered the application of a transparent display as a method to support efficiently this system. When a transparent display applied, the image distortion caused by using a wide-angle lens for parallax secure, and the disc s, and demonstrated the applicability of the technology by developing a prototype.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.27-34
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• 2011

In this paper, we propose an active 3D shape acquisition method based on photometric stereo using camera and flash on a smartphone. Two smartphones are used as the master and slave, in which the slave projects illumination from different locations while the master captures the images and processes photometric stereo algorithm to reconstruct 3D shape. In order to reduce the error, the smartphone's camera is calibrated to overcome the effect of the lens distortion and nonlinear camera sensor response. We apply 5-point algorithm to estimate the pose between smartphone cameras and then estimate lighting direction vector to run the photometric stereo algorithm. Experimental result shows that the proposed system enables us to use smartphone as a 3D camera with low cost and high quality.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.69-79
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• 1999

The research and implementation was preformed on high-resolution CCTV camera with CCD exclusive DSP conventional analog signal processor CCTV camera has its limit on auto exposure(AE), auto white balance(AWB), back light compensation(BLC) processing, severe distortion and noise of image, manual control parameter setting, etc. In our study, to resolve the problems in conventional CCTV camera, we made it possible to control AE, AWB, BLC automatically by the use of the DSP, which are used exclusively in the CCD camera produced domestically, and the microcontroller. And we utilized the function of screen display of microcontroller for the user-friendly interface to control CCD camera. And the electronic variable resister(EVR) was used to avoid setting parameters manually in the level of manufacturing process. As the result, It became possible to control parameters of the camera by program. And the cost-down effect was accomplished by improving the reliability of parameter values and reducing the efforts in setting parameters.

• Journal of Sensor Science and Technology
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• v.7 no.6
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• pp.418-425
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• 1998

Stereo cameras are the most widely used sensing systems for automated machines including robots to interact with their three-dimensional(3D) working environments. The position of a target point in the 3D world coordinates can be measured by the use of stereo cameras and the camera calibration is an important preliminary step for the task. Existing camera calibration techniques can be classified into two large categories - linear and nonlinear techniques. While linear techniques are simple but somewhat inaccurate, the nonlinear ones require a modeling process to compensate for the lens distortion and a rather complicated procedure to solve the nonlinear equations. In this paper, a method employing a neural network for the calibration problem is described for tackling the problems arisen when existing techniques are applied and the results are reported. Particularly, it is shown experimentally that by utilizing the function approximation capability of multi-layer neural networks trained by the back-propagation(BP) algorithm to learn the error pattern of a linear technique, the measurement accuracy can be simply and efficiently increased.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.3
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• pp.56-62
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• 2010

Weakly electric fish uses active sensing to detect the distortion of self-generated electric field in the underwater environments. The active electrolocation makes it possible to identify target objects from the surroundings without vision in the dark sea. Weakly electric fish have many electroreceptors over the whole body surface of electric fish, and sensor readings from a collection of electroreceptors are represented as an electric image. Many researchers have worked on finding features in the electric image to know how the weakly electric fish identify the target object. In this paper, we suggest a new mechanism of how the electrolocation can recognize a given target object among object plants. This approach is based on the differential components of the electric image, and has a potential to be applied to the underwater robotic system for object localization.