• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.117-128
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• 2010

There are many researches related to a simulated shooting training system for replacing the real military and police shooting training. In this paper, we propose the point of impact from a simulated shooting target based on image processing instead of using a sensor based approach. The point of impact is extracted by analyzing the image extracted from the camera on the muzzle of a gun. The final shooting result is calculated by mapping the target and the coordinates of the point of impact. The recognition system is divided into recognizing the projection zone, extracting the point of impact on the projection zone, and calculating the shooting result from the point of impact. We find the vertices of the projection zone after converting the captured image to the binary image and extract the point of impact in it. We present the extracting process step by step and provide experiments to validate the results. The experiments show that exact vertices of the projection area and the point of impact are found and a conversion result for the final result is shown on the interface.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.959-968
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• 2019

In the agricultural industry, wireless sensor network technology has being applied by utilizing various sensors and embedded systems. In particular, a lot of researches are being conducted to diagnose diseases of crops early by using sensor network. There are some difficulties on traditional research how to diagnose crop diseases is not practical for agriculture. This paper proposes the algorithm which enables to investigate and analyze the crop leaf image taken by image camera and detect the infected area within the image. We applied the enhanced k-means clustering method to the images captured at horticulture facility and categorized the areas in the image. Then we used the edge detection and edge tracking scheme to decide whether the extracted areas are located in inside of leaf or not. The performance was evaluated using the images capturing tomato leaves. The results of performance evaluation shows that the proposed algorithm outperforms the traditional algorithms in terms of classification capability.

• Journal of the Korean Geotechnical Society
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• v.38 no.5
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• pp.61-71
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• 2022

Soil color is used to determine soil classification and its physical, chemical, and biological properties. Visual determination is the most commonly used method for identifying soil color. However, it is subjective and, in many cases, non-repeatable. Digital image processing obtains useful information from digital images, accelerates soil classification, and enables the rapid identification of soil types in a field. This study develops a digital image processing-based soil color analysis technology that can consider irregular light conditions in the field. The digital image studio was designed to simulate the characteristics of natural light (illuminance and color temperature). Also, digital images of two soil samples (Jumoonjin sand and Anseong weathered soil) were captured under 12 different light conditions. For the RGB and CIELAB color systems, soil color intensities of 24 images were obtained using digital image processing. CIELAB was suitable for dealing with irregular light conditions in the field.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.751-757
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• 2021

In this paper, we proposed a pipeline system for holographic image production in a web server-based environment. There are time and spatial constraints for the existing holographic image production. The purpose of the proposed system is to obtain high-quality holographic images by reducing accessibility to users. It is a structure in which a video captured by a user in a web environment is transmitted to a server and converted into a frame for holographic image production through post-production. For high-quality holographic image acquisition, post-processing uses a deep learning-based algorithm. The proposed system provides various service tools in the web environment for user convenience. Through this method, the user's accessibility is improved when producing holographic images because images are taken in a web environment rather than in a limited space.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.208-216
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• 2023

The purpose of this study is to present the most appropriate hardware and software configurations to produce a practical SIV (surface image velocimeter). To make a practical SIV, we constructed the system with a CCTV, a water stage gauge, and an analysis software installed on an Android board. The camera captures continuously images for 30 seconds with 2 minute intervals. And the 11-parameter projection method was used in the software that analyzes the captured images to reconstruct the exact measurement points according to the changing water stage. In addition, a spatio-temporal image construction method was developed so that the directions of the images could be arranged in the main flow direction at each measurement point. The surface image velocimeter composed of the proposed method was produced and installed at the Insu Stream, Seoul for a test site. And a result of measurement during a heavy rainfall event showed that the proposed system can measure flow discharge in proper, rapid and continuous manner.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.3
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• pp.397-405
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• 2024

In order to improve the visibility of nighttime thermal infrared images, a simulation method with daytime color images was proposed. As a simulation method consisting of two steps, the daytime thermal infrared image was simulated by learning the unpaired nighttime thermal infrared image and daytime thermal infrared image, then the result was translated into a daytime color image. A temperature change regression equation was constructed and applied to reflect the systematic characteristics of temperature changes in daytime and nighttime images, and day and night simulation and colorization were trained and modeled by CycleGAN. For the experimental area, 100 images were captured and used for training. As a result, the simulation showed an average SSIM of 0.2449 and a PSNR of 51.2254. It was confirmed that the method could simulate complex and detailed features such as vegetation.

• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.25-32
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• 2004

Purpose : The simulator is used to determine patient field and ensure the treatment field, which encompasses the required anatomy during patient normal movement such as during breathing. The latest simulator provide real time display of still, flouroscopic and digitalized image, but conventional simulator is not yet. The purpose of this study is to introduce digital image capture system(DICS) using conventional simulator and clinical case using digital captured still and flouroscopic image. Methods and materials : We connect the video signal cable to the video terminal in the back up of simulator monitor, and connect the video jack to the A/D converter. After connection between the converter jack and computer, We can acquire still image and record flouroscopic image with operating image capture program. The data created with this system can be used in patient treatment, and modified for verification by using image processing software. (j.e. photoshop, paintshop) Result : DICS was able to establish easy and economical procedure. DCIS image was helpful for simulation. DICS imaging was powerful tool in the evaluation of the department specific patient positioning. Conclusion : Because the commercialized simulator based of digital capture is very expensive, it is not easily to establish DICS simulator in the most hospital. DICS using conventional simulator enable to utilize the practical use of image equal to high cost digitalized simulator and to research many clinical cases in case of using other software program.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.51-55
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• 2017

In this paper, we designed a LBS-based smart platform for Lifelog service that can utilize the other's lifelog information. The conventional Lifelog service means that the system records the daily activities of the smart device user so the user can retrieve the early-recorded information later. The proposed Lifelog service platform uses the GPS/UFID location information and the various information extracted from the image as the lifelog data. Further, the proposed Lifelog platform using DB can provide the user with the Lifelog data recorded by the other service user. The system usually provide the other's Lifelog data within the 500m distance from the user and the range of distance can be adjustable. The proposed smart platform based on image recognition for Lifelog can acquire the image from the smart device directly and perform the various image recognition processing to produce the useful image attributes. And it can store the location information, image data, image attributes and the relevant web informations on the database that can be retrieved by the other use's request. The attributes stored and managed in the image information database consist of the followings: Object ID, the image type, the capture time and the image GPS coordinates. The image type attribute has the following values: the mountain, the sea, the street, the front of building, the inside of building and the portrait. The captured image can be classified into the above image type by the pattern matching image processing techniques and the user's direct selection as well. In case of the portrait-attribute, we can choose the multiple sub-attribute values from the shirt, pant, dress and accessory sub-attributes. Managing the Lifelog data in the database, the system can provide the user with the useful additional services like a path finding to the location of the other service user's Lifelog data and information.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.103-111
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• 2007

In this paper, we propose a VLSI architecture of hardware optimized high quality image signal processor for a Single-chip CMOS Image Sensor(CIS). The Single-chip CIS is usually used for mobile applications, so it has to be implemented as small as possible while maintaining the image quality. Several image processing algorithms are used in ISP to improve captured image quality. Among the several image processing blocks, demosaicing and image filter are the core blocks in ISP. These blocks need line memories, but the number of line memories is limited in a low cost Single-chip CIS. In our design, high quality edge-adaptive and cross channel correlation considered demosaicing algorithm is adopted. To minimize the number of required line memories for image filter, we share the line memories using the characteristics of demosaicing algorithm which consider the cross correlation. Based on the proposed method, we can achieve both high quality and low hardware complexity with a small number of line memories. The proposed method was implemented and verified successfully using verilog HDL and FPGA. It was synthesized to gate-level circuits using 0.25um CMOS standard cell library. The total logic gate count is 37K, and seven and half line memories are used.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.52-59
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• 2009

In general, methods based on histogram or a correction of gamma curve are usually utilized to enhance the contrast of captured image in the dark scene. These methods are efficient to enhance the contrast globally, however, they locally induced the low quality of image. Recently, to resolve the problem, the multi-scaled refiner algorithm improving the contrast with locally averaged lightness is proposed. However, estimating the locally averaged lightness, if there is the object with a high saturated color, the color distortion might be induced by the color of object. Thus, in this paper, the dominant chromaticity of image is estimated to correct the locally averaged lightness in multi-scaled retinex algorithm. Because the average chromaticity of image includes the chromaticity of illumination, the dominant chromaticity is estimated with dividing the average chromaticity of image by the estimated chromaticity of illumination from highlight region. In addition, to improve the lower chroma by multi-scaled retinex algorithm generally, the chroma was compensated preserving the hue in the CIELAB color space.