• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.441-443
• /
• 2018

This paper deals with the analysis of leg motion using RGB image. We used RGB image as gait analysis element by using BMC(Background Model Challenge) method and by using combining object recognition segmentation algorithm and attitude detection algorithm. It is considered that gait analysis incorporating image can be used as a parameter for classification of gait pattern recognition and abnormal gait.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.6
• /
• pp.555-563
• /
• 2018

Thermal infrared images have the characteristic of being able to detect objects that can not be seen with the naked eye and have the advantage of easily obtaining information of inaccessible areas. However, TIR (Thermal InfraRed) images have a relatively low spatial resolution. In this study, the applicability of the pansharpening algorithm used for satellite imagery on images acquired by the UAV (Unmanned Aerial Vehicle) was tested. RGB image have higher spatial resolution than TIR images. In this study, pansharpening algorithm was applied to TIR image to create the images which have similar spatial resolution as RGB images and have temperature information in it. Experimental results show that the pansharpening algorithm using the PC1 band and the average of RGB band shows better results for the quantitative evaluation than the other bands, and it has been confirmed that pansharpening results by ATWT (${\grave{A}}$ Trous Wavelet Transform) exhibit superior spectral resolution and spatial resolution than those by HPF (High-Pass Filter) and SFIM (Smoothing Filter-based Intensity Modulation) pansharpening algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.5C
• /
• pp.513-519
• /
• 2007

Color correlogram is widely used in content-based image retrieval (CBIR) because it extracts not only the color distribution of pixels in images like color histogram, but also extracts the spatial information of pixels in the images. The color correlogram uses single color space. Therefore, the color correlograms does not have robust discriminative features. In this paper, we use both RGB and HSV color spaces together for the color correlogram to achieve better discriminative features. The proposed algorithm is tested on a large database of images and the results are compared with the single color space color correlogram. In simulation results, the proposed algorithm 5.63 average retrieval rank less than single color space correlogram.

• Journal of Urban Science
• /
• v.6 no.2
• /
• pp.17-27
• /
• 2017

Recently, civil complaints have increased due to water pollution and bad smell in rivers. Therefore, attention is focused on improving the river environment. The purpose of this study is to acquire RGB and thermal infrared images using UAV for sewage outlet and to monitor the status of stream pollution and the applicability UAV based images for river embankment maintenance plan was examined. The accuracy of the 3D model was examination by SfM(Structure from Motion) based images analysis on river embankment maintenance area. Especially, The wastewater discharged from the factory near the river was detected as an thermal infrared images and the flow of wastewater was monitored. As a result of the study, we could monitor the cause and flows of wastewater pollution by detecting temperature change caused by wastewater inflow using UAV images. In addition, UAV based a high precision 3D model (DTM, Digital Topographic Map, Orthophoto Mosaic) was produced to obtain precise DSM(Digital Surface Model) and vegetation cover information for river embankment maintenance.

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

• The KIPS Transactions:PartB
• /
• v.14B no.6
• /
• pp.445-452
• /
• 2007

We proposed a detection scheme of weather information in CCTV video images in this paper. The scheme obtains the RGB distribution of shiny day and divide a target image into cloud, rain, snow and for RGB distributions. shiny day RGB distribution. Our scheme designed systematically to detection and separation special characteristics of images from complex weather information. Our algorithm has less overhead than the previous methods to use weather database DB at the view of time and space. And our algorithm can be use in real world system with low cost of implementation. Also, our algorithm use informations of temperature, humidity, date, and time to detect the information of weather with high quality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2015.07a
• /
• pp.457-459
• /
• 2015

본 논문에서는 원의 호 곡선에 따라 배치된 다중 RGB 카메라 영상으로 생성한 깊이 지도를 정렬하는 방법을 제안한다. 원의 호 곡선에 따라 배치된 카메라는 각 카메라의 광축이 한 점으로 만나서 수렴하는 형태가 이상적이다. 그러나 카메라 파라미터를 살펴보면 광축이 서로 수렴하지 않는다. 또한 카메라 파라미터는 오차가 존재하고 내부 파라미터도 서로 다르기 때문에 각 카메라 영상들은 수평과 수직 오차가 발생한다. 이와 같은 문제점을 해결하기 위해 첫 번째로 광축이 한 점으로 수렴하기 위해서 카메라 외부 파라미터를 보정하여 깊이 영상 정렬을 하였다. 두 번째로 내부 파라미터를 수정하여 각 깊이 영상들의 수평과 수직 오차를 감소시켰다. 일반적으로 정렬된 깊이 지도를 얻기 위해서는 초기 RGB 카메라 영상으로 정렬을 수행하고 그 결과 영상으로 깊이 영상을 생성한다. 하지만 RGB 영상으로 카메라의 회전과 위치를 보정하여 정렬하면 카메라 위치 변화에 따른 깊이 지도 변화값 적용이 복잡해 진다. 즉 정렬 계산 과정에서 소수점 단위 값이 사라지기에 최종 깊이 지도의 값에 영향을 미친다. 그래서 RGB 영상으로 깊이 지도를 생성하고 그것을 처음 RGB 카메라 파라미터로 워핑(warping)하였다. 그리고 워핑된 깊이 지도 값을 가지고 정렬을 수행하였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.419-420
• /
• 2020

본 논문에서는 불법복제 영상 판단을 위한 RGB 변위값 측정을 통한 360도 영상 식별 기준 키 프레임 선정 방법을 제안한다. 방송 프로그램이나 영화 등과 같은 콘텐츠는 인터넷들을 통하여 국내뿐만 아니라 해외로도 대량 불법 유통됨으로써 국가적으로 큰 손실이 발생하고 있다. 본 논문에서는 이러한 불법복제 여부를 빠른 속도로 판단하기 위한 방법으로 360도 영상에서 추출된 각각의 프레임에서 RGB 변위값을 측정하여 동일한 장면으로 인식되는 프레임을 하나로 묶어 해당 장면의 키 프레임으로 선정한다. 본 논문에서 제안한 방법은 불법복제 영상의 판단 시간을 단축시키고 판단 정확도를 향상시킬 수 있는 효과가 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.162-163
• /
• 2012

In this paper, we propose a synthesis method of elemental images from Kinect images for 3D integral imaging display. Since RGB images and depth image obtained from Kinect are not able to display 3D images in integral imaging system, we need transform the elemental images in integral imaging display. To do so, we synthesize the elemental images based on the geometric optics mapping from the depth plane images obtained from RGB image and depth image. To show the usefulness of the proposed system, we carry out the preliminary experiments using the two person object and present the experimental results.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.34 no.5
• /
• pp.1645-1653
• /
• 2014

In general, RGB, NIR, and thermal images are used for obtaining geospatial data. Such multiband images are collected via devices mounted on satellites or manned flights, but do not always meet users' expectations, due to issues associated with temporal resolution, costs, spatial resolution, and effects of clouds. We believe high-resolution, multiband images can be obtained at desired time points and intervals, by developing a payload suitable for a low-altitude, auto-piloted UAV. To achieve this, this study first established a low-cost, high-resolution multiband image collection system through developing a sensor and a payload, and collected geo-referencing data, as well as RGB, NIR and thermal images by using the system. We were able to obtain a 0.181m horizontal deviation and 0.203m vertical deviation, after analyzing the positional accuracy of points based on ortho mosaic images using the collected RGB images. Since this meets the required level of spatial accuracy that allows production of maps at a scale of 1:1,000~5,000 and also remote sensing over small areas, we successfully validated that the payload was highly utilizable.