• Proceedings of the Korea Multimedia Society Conference
• /
• 2002.05c
• /
• pp.272-276
• /
• 2002

본 논문은 영역을 병합할 때 두 영역의 색상 차를 영역 병합의 제한 조건으로 사용하는 칼라 영상 분할 기법을 제안하였다. 이는 먼저 영역의 경계선 정보를 잘 보존하기 위해서 RGB 공간상에서 수리형태학 필터와 변형된 워터쉐드 알고리즘을 이용하여 칼라 영상을 과분할 한다. 그리고 영역 간의 색상 차를 제한 조건으로 사용하는 영역 병합 과정을 반복 수행하여 칼라 영상의 분할 결과를 얻는다. 이는 인간 시각 시스템이 색상, 채도, 명도의 형태로 색을 구분하는 것을 기반으로 한다. 명도가 낮지 않는 경우에 색차 보다 색상 차가 중요한 요소로 작용하기 때문에 이를 영역 병합의 제한 조건으로 사용한다. 실험결과에서 제안된 칼라 영상 분할 기법은 다양한 칼라 영상에 대하여 적은 개수의 영역으로 동일한 색상을 가지는 영역의 경계선을 유지하는 효율적인 분할을 보임을 확인하였다.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2003.05b
• /
• pp.385-388
• /
• 2003

영상의 에지는 입력 영상에 대한 중요 정보들을 가지고 있으며, 에지 추출은 영상인식의 성능을 좌우하는 중요 요소이다. 영상 에지 추출은 영상 분할의 첫 번째 단계이며, 영상의 구성을 결정하기 위해서 화소들을 하나의 영역으로 만드는데 사용되고 있다. 또한 에지 강도를 갖고 있는 모든 에지들을 검출하기 위해 많은 방법들이 제안되었다 기존의 에지 짐출은 흑백영상의 명암도의 변화에 국한되어 있었다 그러나 칼라영상을 이용하여 에지를 추출하는 경우에는 흑백영상보다 이용할 수 있는 정보가 많을 뿐 아니라 인간의 시각체계와도 유사하여 보다 나은 에지 추출을 기대할 수 있다. 본 논문에서는 칼라영상에서 직접적으로 얻을 수 있는 RGB 정보 중 광도를 분리하여 사용하는 YCbCr성분을 이용하여, 기존의 기울기연산자나 표면접합 템플릿에 의한 에지 추출이 아닌 3$\times$3 마스크안의 데이터값의 차에 따라 가변적으로 변하는 BBM템플릿을 제안하였다. 제안된 가변 BBM템플릿은 모의 실험한 결과 기존의 Sobel, Preweet, Roberts 같은 연산 템플릿보다 성능이 우수함을 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.305-307
• /
• 2009

본 논문에서는 기존의 퍼지 논리를 이용한 필터링 알고리즘의 문제점을 개선하는 동시에 컬러 영상에 적용할 수 있는 퍼지 필터 알고리즘을 제안한다. 제시된 퍼지 필터 알고리즘은 영상의 RGB 컬러 정보를 각각의 R, G, B 채널 영상으로 분리하고, 각 채널 영상에서 마스크가 위치한 기준 픽셀의 잡음 가능성 정도를 퍼지 논리에 적용하여 판단한다. 잡음 정도에 따라서 출력 영상의 화소값을 평균값 또는 중간값으로 결정한다. 제안된 방법을 잡음이 존재하는 칼라 영상에 적용한 결과, 단색 정보를 기준으로 처리하는 기존의 퍼지 필터 방법에 비해서 효과적인 것을 확인하였다.

• Atmosphere
• /
• v.18 no.1
• /
• pp.1-14
• /
• 2008

The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images composed of red, green and blue (RGB). The true color image is obtained by the Skyview, an all-sky imager taking pictures of sky, at the Science Building of Yonsei University, Seoul for a year in 2006. The principle of distinguishing clear sky from cloudy sky lies in the fact that the spectral characteristics of light scattering is different for air molecules and cloud. The result of Skyview's algorithm showed about 77% agreement between the observed cloud amount and the calculated, for the error range, the difference between calculated and observed cloudiness, within ${\pm}2$. Seasonally, the best accuracy of about 83% was obtained within ${\pm}2$ range in summer when the cloud amounts are higher, thus better signal-to-noise ratio. Furthermore, as the sky turbidity increased, the error also increased because of increased scattering which can explain the large error in spring. The algorithm still need to be improved in classifying sky condition more systematically with other complimentary instruments to discriminate thin cloud from haze to reduce errors in detecting clouds.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.7
• /
• pp.1702-1708
• /
• 2013

OLED has good efficiency of power consumption by having no power consumption from black color as different with LCD. when it has white color, all RGB pixel should be glowing with high power consumption and that can make it has short life time. This paper suggest the way of low power consumption for OLED panel using adaptive luminance enhancement with color compensation and implement it as hardware. This way which is based on luminance information of input image makes converted luminance value from each pixel in real time. There is with using the basic idea of chromaticity reduction algorithm, showing new algorithm of color correction. And performance of proposed method was confirmed by comparing the conventional method in experiments about 48.43% current reduction. The proposed method was designed by Verilog HDL and was verified by using OpenCV and Windows Program.

• Journal of the Microelectronics and Packaging Society
• /
• v.22 no.1
• /
• pp.15-19
• /
• 2015

We demonstrated an inspection system for detecting discoloration of PCB Cu ball pad with an OSP surface finish. Though the OSP surface finish has many advantages such as eco-friendly and low cost, however, it often shows a discoloration phenomenon due to a heating process. In this study, the discoloration was analyzed with device-independent CIELAB color space. First of all, the PCB samples were inspected with standard lamps and CCD camera. The measured data was processed with Labview program for detecting discoloration of Cu ball pad. From the original PCB sample image, the localized Cu ball pad image was selected to reduce the image size by the binarization and edge detection processes and it was also converted to device-independent CIELAB color space using $3{\times}3$ conversion matrix. Both acquisition time and false acceptance rate were significantly reduced with this proposed inspection system. In addition, $L^*$ and $b^*$ values of CIELAB color space were suitable for inspection of discoloration of Cu ball pad.

• Journal of the Korean Applied Science and Technology
• /
• v.40 no.6
• /
• pp.1580-1588
• /
• 2023

The desire for clear and clean skin is universal among both men and women. Women, in particular, seek the help of foundation to achieve beautiful and transparent skin. The choice of foundation is not determined by the race of an individual; instead, it varies based on personal skin color and undertone. Therefore, there is a need to surpass the stereotype of using foundation colors based on racial discrimination. The purpose of this study is to randomly select cosmetics brands from Korea, China, Japan, the United States, France, and the United Kingdom, considering the impact of each photo, environment, and equipment. The objective is to understand the differences in skin tones in foundation advertisement model images on websites. Analyzing the RGB values of foundation colors for each brand revealed that in Korea, the colors were 8.75R, 1.25YR, 2.5YR, 3.75YR, 5YR, and 6.25YR. Chinese brands showed similar colors with 2.5YR, 3.75YR, 5YR, 6.25YR, and 10YR. Japanese brands displayed colors such as 7.5R, 8.75R, 10R, 5YR, 6.25YR, and 7.5YR. American brands presented colors like 6.25R, 8.75R, 10R, 2.5YR, 3.75YR, 5YR, 6.25YR, 7.5YR, and 10YR. French brands featured 10R, 1.25YR, 3.75YR, 5YR. Lastly, British brands displayed 2.5YR, 3.75YR, 7.5YR. As a follow-up study, in-depth research on the reshaping and color changes of foundation over time is recommended. It is hoped that this research will serve as fundamental data for makeup companies' marketing and contribute to the development of both domestic and international color cosmetics markets.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.4
• /
• pp.83-92
• /
• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• Journal of Internet Computing and Services
• /
• v.16 no.2
• /
• pp.49-55
• /
• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Korean Journal of Remote Sensing
• /
• v.32 no.2
• /
• pp.87-96
• /
• 2016

Red tide, causes aquaculture industry the damages in Korea every summer, was usually detected by using satellite, aquaculture information was difficult to detect by using satellite. Therefore, we suggests the method for detecting the red tide using the coastal observation and the product from the unmanned aerial Vehicle. As a result, we obtained the high resolution unmanned aerial Vehicle images, detected the red tide by using the unsupervised classification from the true color images and the simple algorithm from the RGB color images. Compared the previous color images, unmanned aerial Vehicle images were clearly classified the ocean color, we were able to identify the red tide distribution in sea surface. These methods were determined to accurately monitor the red tide distribution on the aquaculture fields in the coastal waters where is established the aquaculture.