• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11C
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• pp.1040-1048
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• 2009

This paper proposes an auto flesh tone balance algorithm for the picture that is taken for people. General white balance algorithms bring neutral region into focus. But, other objects can be basis if its spectral reflectance is known. In this paper the basis for white balance is human face. For experiment, first, transfer characteristic of image sensor is analyzed and camera output RGB on average face chromaticity under standard illumination is calculated. Second, Output rate for the image is adjusted to make RGB rate for the face photo area taken under unknown illumination RGB rate that is already calculated. Input tri-stimulus XYZ can be calculated from camera output RGB by camera transfer matrix. And input tri-stimulus XYZ is transformed to standard color space (sRGB) using sRGB transfer matrix. For display, RGB data is encoded as eight-bit data after gamma correction. Algorithm is applied to average face color that is light skin color of Macbeth color chart and average color of various face colors that are actually measured.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.93-96
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• 2006

2D 및 입체 영상 콘텐츠의 공급이 많아지면서 실감 콘텐츠에 대한 관심이 더욱 높아지고 있다. 실감 콘텐츠는 다시점 카메라로부터 획득한 다시점 비디오, 깊이 카메라에서 얻은 RGB 영상과 컴퓨터 그래픽스와 같은 synthetic data를 합성하여 보다 실감나게 제작된다. 다시점 카메라를 이용하면 다시점 비디오를 쉽게 획득할 수 있으나 제작비용이 많이 들고, 깊이 카메라를 사용하면 시스템 구성은 상대적으로 용이하나 시점 영상이 하나라는 단점이 있다. 본 논문에서는 깊이 카메라에서 얻은 RGB 텍스쳐 데이터와 깊이 데이터로부터 가상 다시점 영상을 생성하고, 생성된 영상에 컴퓨터 그래픽스를 합성하는 방법을 제안한다. 제안한 방법은 다시점 카메라 시스템을 사용하지 않고도 시점에 따른 가상 시점 화상을 용이하게 제작하여 그래픽 객체를 합성한다. 합성된 다시점 3D 모니터나 입체 모니터를 이용하여 3차원으로 실감나게 시청할 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.248-249
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• 2022

In this paper, we propose a method for classifying and tracking objects based on information of multiple users obtained using RGB-D cameras. The 3D information and color information acquired through the RGB-D camera are acquired and information about each user is stored. We propose a user classification and location tracking algorithm in the entire image by calculating the similarity between users in the current frame and the previous frame through the information on the location and appearance of each user obtained from the entire image.

• Korean Journal of Optics and Photonics
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• v.31 no.2
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• pp.71-80
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• 2020

In this article, we suggest a new method for measuring an aerosol's extinction coefficient using a commercial camera. For a given image, we choose three pixel-points that are imaged for the same kinds of objects located in similar directions. We suggest and calculate aerosol extinction coefficients from these RGB gray levels and the different distances of the three objects. To compare our measurement results, we also measure extinction coefficients using lidar. Finally, we find that there are meaningful and sensible correlations between these two measurements, with a correlation coefficient of 0.86. We measure the aerosol extinction coefficient at three different RGB wavelengths using the same method. From these aerosol extinction coefficients at three different wavelengths, we find that the Angstrom exponent ranges from 0.7 to 1.6 over a full daytime period. We believe that these Angstrom exponents can give important information about the size of the fine particles.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.395-397
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• 1999

디지털 카메라에 의해 획득된 RGB 칼라 신호는 디지털 카메라의 하드웨어적인 특성에 따라 서로 다른 값을 가지는 장비 의존적(Device Dependent) 특성을 가지며, 칼라 운영 시스템(CMS; Color Management System)이 프로파일 연결 칼라 공간(PCS:Profile Connection Space)으로 사용하는 CIE XYZ 칼라 공간에 대해 비선형적인 특성을 가진다. 본 논문에서는 디지털 카메라의 RGB 칼라 신호를 장비 독립적(Device Independent)인 CIE XYZ 칼라 공간으로 변환하는 변환 행렬을 구하는 방법을 제안한다. 변환 행렬은 비선형 다항식을 이용하여 3$\times$m의 변환 행렬을 구하고, 실험에 사용되는 칼라 샘플의 수에 따른 일반화(Generalization) 성능을 평가한다.

• Journal of IKEEE
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• v.23 no.1
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• pp.44-52
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• 2019

We implement an educational indoor autonomous mobile robot system that integrates LiDAR sensing information with RGB-D camera image information and exploits the integrated information. This system uses the existing sensing method employing a LiDAR with a small number of scan channels to acquire LiDAR sensing information. To remedy the weakness of the existing LiDAR sensing method, we propose the 3D structure recognition technique using depth images from a RGB-D camera and the deep learning based object recognition algorithm and apply the proposed technique to the system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.193-202
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• 2004

This paper presents a novel histogram and color information based algorithm for detecting and tracking multiple pedestrians from a moving camera. In the proposed method, RGB color histogram is used to detect adjacent pedestrians and RGB mean value is used to track detected pedestrians. Therefore, our algorithm detect contiguous or a few occluded pedestrians and track in case pedestrian's shape change. The experimental results on our test sequences demonstrate the high efficiency of our method.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.626-629
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• 2019

운전 중 운전자의 눈부심은 도로 상황 인식에 대해 악영향을 미치고, 운전자가 운전 중 필요로 하는 도로의 요소들을 적절히 고려할 수 있는 시간의 부재로 이어져 결국 교통사고로까지 이어질 수 있다. 본 논문에서는 자동차 운전자를 위한 단일 RGB 카메라와 스마트 필름 기반 눈부심 측정 및 완화 기법으로, RGB 카메라를 이용한 눈부심 검출 및 스마트 필름과의 연동으로 눈부심을 완화할 수 있는 기법에 대해 제안한다. 추후 본 기법으로 운전 중 다양한 원인으로 인해 발생할 수 있는 눈부심과 그에 따른 교통사고의 위험을 경감시키기 위한 도구로 활용될 수 있을 것으로 기대한다.

• 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 Korea Institute of Information and Communication Engineering
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• v.25 no.5
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• pp.637-644
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• 2021

In general, in the fields of computer vision, robotics, and augmented reality, the importance of 3D space and 3D object detection and recognition technology has emerged. In particular, since it is possible to acquire RGB images and depth images in real time through an image sensor using Microsoft Kinect method, many changes have been made to object detection, tracking and recognition studies. In this paper, we propose a method to improve the quality of 3D reconstructed images by processing images acquired through a depth-based (RGB-Depth) camera on a multi-view camera system. In this paper, a method of removing noise outside an object by applying a mask acquired from a color image and a method of applying a combined filtering operation to obtain the difference in depth information between pixels inside the object is proposed. Through each experiment result, it was confirmed that the proposed method can effectively remove noise and improve the quality of 3D reconstructed image.