• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.411-417
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• 2021

The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

• Bulletin of the Korean Chemical Society
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• v.30 no.12
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• pp.3031-3033
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• 2009

A new colorimetric anion sensor 1 has been synthesized based on both Fat brown RR dye and a nitrophenyl group. This new receptor 1 could recognize the presence of fluoride ion effectively and selectively by the change of color of solution. In addition, receptor 1 shows higher affinity for acetate, dihydrogenphosphate, and hydrogensulfate than the other anions such as chloride, bromide, iodide, perchlorate, and nitrate in acetonitrile.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.679-686
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• 2022

In this paper, we implemented an algae removal device that recognizes and removes algae existing in water using Raspberry Pi camera and DO (Dissolved Oxygen) sensor. The Raspberry Pi board recognizes the color of green algae by converting the RGB values obtained from the camera into HSV. Through this, the location of the algae is identified and when the amount of dissolved oxygen's decrease at the location is more than the reference value using the DO sensor, the algae removal device is driven to spray the algae removal solution. Raspberry Pi's camera uses OpenCV, and the motor movement is controlled according to the output value of the DO sensor and the result of the camera's green algae recognition. Algae recognition and spraying of algae removal solution were implemented through Arduino and Raspberry Pi, and the feasibility of the proposed portable algae removal device was verified through experiments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.634-638
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• 2018

Haze is a factor that degrades the performance of various image processing algorithms, such as those for detection, tracking, and recognition using an electro-optical sensor. For robust operation of an electro-optical sensor-based unmanned system used outdoors, an algorithm capable of effectively removing haze is needed. As a haze removal method using a single electro-optical sensor, the dark channel prior using statistical properties of the electro-optical sensor is most widely known. Previous methods used a square filter in the process of obtaining a transmission using the dark channel prior. When a square filter is used, the effect of removing haze becomes smaller as the size of the filter becomes larger. When the size of the filter becomes excessively small, over-saturation occurs, and color information in the image is lost. Since the size of the filter greatly affects the performance of the algorithm, a relatively large filter is generally used, or a small filter is used so that no over-saturation occurs, depending on the image. In this paper, we propose an improved haze removal method using color image segmentation. The parameters of the color image segmentation are automatically set according to the information complexity of the image, and the over-saturation phenomenon does not occur by estimating the amount of transmission based on the parameters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.493-497
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• 2015

This study was started with concern about problem of increasing physical and personal injury caused by traffic accidents, despite of technological advances in transportation. As the vehicles, which is currently produced, informs the driver only detecting the proximity of an object by the front and rear sensor, this study implemented the color detection algorithm, the circular shape recognition algorithm, and the distance recognition algorithm and built the accident prevention beyond accident perception, which commends to avoid the object or to stop the robot, if object was detected by algorithms. For the simulation, we made the Arduino vehicle robot equipped with compact wireless communication camera and confirmed that the robot successfully avoids an object or stops itself in simulated driving.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.46-54
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• 2008

Most commercial CCD/CMOS image sensors have CFA(Color Filter Array) where each pixel gathers light of a selective color to reduce the sensor size and cost. There are many algorithms proposed to reconstruct the original clolr image by adopting pettern recognition of regularization methods to name a few. However the resulting image still suffer from errors such as flase color, zipper effect. In this paper we propose an adaptive edge weight demosaicking algorithm that is based on POCS(Projection Onto Convex Sets) not only to improve the entire image's PSNR but also to reduce the edge region's errors that affect subjective image quality. As a result, the proposed algorithm reconstruct better quality images especially at the edge region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1317-1324
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• 2016

Utilizing the Arduino platform to express the emotions that reflect the colors expressed the jewelry. Emotional color expression utilizes Plutchik's Wheel of Emotions model was applied to the similarity of emotions and colors. It receives the recognized value from the temperature, lighting, sound, pulse sensor and gyro sensor of a smart jewelery that can be easily accessible from your smartphone processes that recognize and process the emotion applied the rules of inference based on ontology. The emotional feelings color depending on the color looking for the emotion seen in context and applied to the smart LED jewelry. The emotion and the color combination of contextual information extracted from the recognition sensors are reflected in the built-in smart LED Jewelry depending on the emotions of the wearer. Take a light plus the emotion in a smart jewelery can represent the emotions of the situation, the doctor will be able to be a tool of representation.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.933-940
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• 2022

In this paper, the algorithm was developed to recognize hand 3D position through 2D image sensor and implemented a system to remotely control the 6 d.o.f. robot arm by using it. The system consists of a camera that acquires hand position in 2D, a computer that controls robot arm that performs movement by hand position recognition. The image sensor recognizes the specific color of the glove putting on operator's hand and outputs the recognized range and position by including the color area of the glove as a shape of rectangle. We recognize the velocity vector of end effector and control the robot arm by the output data of the position and size of the detected rectangle. Through the several experiments using developed 6 axis robot, it was confirmed that the 6 d.o.f. robot arm remote control was successfully performed.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.229-235
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• 2011

To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human's body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.