• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.174-182
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• 2015

In this paper, we developed the small size RGB sensor that recognizes a long distance using a low-cost color sensor. Light receiving portion of the sensor was used as a camera lens for far distance recognition, and illuminating unit was increased the strength of the light by using a high-power white LED and a lens mounted on the reflector. RGB color recognition algorithm consists of the learning process and the realtime recognition process. We obtain a normalized RGB color reference data in the learning process using the specimens painted with target colors, and classifies the three colors using the Mahalanobis distance in recognition process. We apply the developed the RGB color recognition sensor to a prototype of the part classification system and evaluate the performance of its.

• Smart Media Journal
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• v.12 no.9
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• pp.134-141
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• 2023

In this paper, we propose a ToF-Stereo fusion sensor system for 3D space scanning that increases the recognition rate of 3D objects, guarantees object detection quality, and is robust to the environment. The ToF-Stereo sensor fusion system uses a method of fusing the sensing values of the ToF sensor and the Stereo RGB sensor, and even if one sensor does not operate, the other sensor can be used to continuously detect an object. Since the quality of the ToF sensor and the Stereo RGB sensor varies depending on the sensing distance, sensing resolution, light reflectivity, and illuminance, a module that can adjust the function of the sensor based on reliability estimation is placed. The ToF-Stereo sensor fusion system combines the sensing values of the ToF sensor and the Stereo RGB sensor, estimates the reliability, and adjusts the function of the sensor according to the reliability to fuse the two sensing values, thereby improving the quality of the 3D space scan.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.95-114
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• 2022

This study presented the possibility of automatic frost observation and the related image data acquisition through the design and installation of a Multiple-sensor based Frost Observation System (MFOS). The MFOS is composed of an RGB camera, a thermal camera and a leaf wetness sensor, and each device performs complementary roles. Through the test operation of the equipment before the occurrence of frost, the voltage value of the leaf wetness sensor increased when maintaining high relative humidity in the case of no precipitation. In the case of Gapyeong- gun, the high relative humidity was maintained due to the surrounding agricultural waterways, so the voltage value increased significantly. In the RGB camera image, leaf wetness sensor and the surface were not observed before sunrise and after sunset, but were observed for the rest of the time. In the case of precipitation, the voltage value of the leaf wetness sensor rapidly increased during the precipitation period and decreased after the precipitation was terminated. In the RGB camera image, the leaf wetness sensor and surface were observed regardless of the precipitation phenomenon, but the thermal camera image was taken due to the precipitation phenomenon, but the leaf wetness sensor and surface were not observed. Through, where actual frost occurred, it was confirmed that the voltage value of leaf wetness sensor was higher than the range corresponding to frost, but frost was observed on the surface and equipment surface by the RGB camera.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.4
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• pp.42-49
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• 2009

This paper proposes a driving current control method for a back light unit (BLU), consisting of red, green, and blue (RGB) light-emitting diodes (LEDs), whereby an RGB optical sensor is used to check the output color stimulus variation to enable a time-stable color stimulus for light emission by the RGB LED BLU. First, to obtain the present color stimulus information of the RGB LED BLU, an RGB to XYZ transform matrix is derived to enable CIEXYZ values to be calculated for the RGB LED BLU from the output values of an RGB optical sensor. The elements of the RGB to XYZ transform matrix are polynomial coefficients resulting from a polynomial regression. Next, to obtain the proper duty control values for the current supplied to the RGB LEDs, an XYZ to Duty transform matrix is derived to calculate the duty control values for the RGB LEDs from the target CIEXYZ values. The data used to derive the XYZ to Duty transform matrix are the CIEXYZ values for the RGB LED BLU estimated from the output values of the RGB optical sensor and corresponding duty control values applied to the RGB LEDs for the present, first preceding, and second preceding sequential check points. With every fixed-interval check of the color stimulus of the RGB LED BLU, the XYZ to Duty transform matrix changes adaptively according to the present lighting condition of the RGB LED BLU, thereby allowing the RGB LED BLU to emit the target color stimulus in a time-stable format regardless of changes in the lighting condition of the RGB LEDs.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.872-875
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• 2014

재난방지 및 구호에 사용되는 로봇의 주된 목적은 인간이 직접적인 접근을 할 수 없는 지역을 사전에 탐사하여 인간으로 하여금 올바른 판단을 돕기 위함에 있다. 하지만, 재난 지역에서는 통신장애 문제나, 육안 식별이 불가능한 상황, 원격조정을 통하여 로봇이 업무 수행에 상당한 제약을 받는다. 이 문제를 해결하기 위해 "LED-RGB 칼라센서를 이용한 상호위치 인식 방법연구"[1]을 수행하였으나, RGB의 인식거리가 상당히 짧고, 판단이 모호한 단점이 발생하였다. 따라서 본 연구에서는 이를 개선한 RGB-D센서를 이용하여 RGB의 인식거리를 증가시켰다. 또한 더욱 높은 정확성을 이용하기 위해, Depth를 사용하여 사물들의 특징점들을 랜드마크로 하고 랜드마크로부터의 상대위치를 파악하여 위치를 추정하는 방법을 제안하고자 한다. 마지막으로 상호인식 알고리즘을 이전 방식과 비교하고자 한다.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.48-52
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• 2023

Many studies have been conducted to ensure that Visual Place Recognition is reliable in various environments, including edge cases. However, existing approaches use visible imaging sensors, RGB cameras, which are greatly influenced by illumination changes, as is widely known. Thus, in this paper, we use an invisible imaging sensor, a long wave length infrared camera (LWIR) instead of RGB, that is shown to be more reliable in low-light and highly noisy conditions. In addition, although the camera sensor used to solve this problem is an LWIR camera, but since the thermal image is converted into RGB image the proposed method is highly compatible with existing algorithms and databases. We demonstrate that the proposed method outperforms the baseline method by about 0.19 for recall performance.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.70-76
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• 2020

Multi-floor navigation of a mobile robot requires a technology that allows the robot to safely get on and off the elevator. Therefore, in this study, we propose a method of recognizing the elevator from the current position of the robot and estimating the location of the elevator locally so that the robot can safely get on the elevator regardless of the accumulated position error during autonomous navigation. The proposed method uses a deep learning-based image classifier to identify the elevator from the image information obtained from the RGB-D sensor and extract the boundary points between the elevator and the surrounding wall from the point cloud. This enables the robot to estimate the reliable position in real time and boarding direction for general elevators. Various experiments exhibit the effectiveness and accuracy of the proposed method.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.121-128
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• 2018

Obstacle avoidance is one of the most important parts of autonomous mobile robot. In this study, we proposed safe and efficient local path planning of robot for obstacle avoidance. The proposed method detects and tracks obstacles using the 3D depth information of an RGB-D sensor for path prediction. Based on the tracked information of obstacles, the paths of the obstacles are predicted with probability circle-based spatial search (PCSS) method and Gaussian modeling is performed to reduce uncertainty and to create the cost function of caution. The possibility of collision with the robot is considered through the predicted path of the obstacles, and a local path is generated. This enables safe and efficient navigation of the robot. The results in various experiments show that the proposed method enables robots to navigate safely and effectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.226-235
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• 2023

This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.1049-1054
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• 2011

Color is discerned due to the reflectance of object and its hue is determined by the Ratio of RGB spectrum. The aim of this study is to evaluate the Color information using by the optical system in terms of convenience and simplicity. Firstly, the differential Ratio of RGB is evaluated by photodiode Sensor which achieves a high efficiency with quick tranducer output. To extract the information of RGB Ratio, light emitting diode is built in Color sensing system with photodiode. Our proposed method is very economical, simple, and convenient. Our results can be applied to confirm the accurate information of Color in the research environments and commercial purposes. Thus RGB information can be determined subjectively and thus, the inherent characteristic of Color will be revealed precisely and its related features can be resolved in a real time mode.