• Title/Summary/Keyword: HSV Color

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PID Controled UAV Monitoring System for Fire-Event Detection (PID 제어 UAV를 이용한 발화 감지 시스템의 구현)

  • Choi, Jeong-Wook;Kim, Bo-Seong;Yu, Je-Min;Choi, Ji-Hoon;Lee, Seung-Dae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.1
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    • pp.1-8
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    • 2020
  • If a dangerous situation arises in a place where out of reach from the human, UAVs can be used to determine the size and location of the situation to reduce the further damage. With this in mind, this paper sets the minimum value of the roll, pitch, and yaw using beta flight to detect the UAV's smooth hovering, integration, and derivative (PID) values to ensure that the UAV stays horizontal, minimizing errors for safe hovering, and the camera uses Open CV to install the Raspberry Pi program and then HSV (color, saturation, Brightness) using the color palette, the filter is black and white except for the red color, which is the closest to the fire we want, so that the UAV detects the image in the air in real time. Finally, it was confirmed that hovering was possible at a height of 0.5 to 5m, and red color recognition was possible at a distance of 5cm and at a distance of 5m.

A Black and White Comics Generation Procedure for the Video Frame Image using Region Extension based on HSV Color Model (HSV 색상 모델과 영역 확장 기법을 이용한 동영상 프레임 이미지의 흑백 만화 카투닝 알고리즘)

  • Ryu, Dong-Sung;Cho, Hwan-Gue
    • Journal of KIISE:Computer Systems and Theory
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    • v.35 no.12
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    • pp.560-567
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    • 2008
  • In this paper, we discuss a simple and straightforward binarization procedure which can generate black/white comics from the video frame image. Generally, the region of human's skin is colored white or light gray, while the dark region is filled with the irregular but regular patterns like hatching in most of the black/white comics. Note that it is not enough for simple threshold method to perform this work. Our procedure is decoupled into four processes. First, we use bilateral filter to suppress noise color variation and reserve boundaries. Then, we perform mean-shift segmentation for each similar colored pixels to be clustered. Third, the clustered regions are merged and extended by our region extension algorithm considering each color of their regions. Finally, we decide which pixels are on or off using by our dynamic binarization method based on the HSV color model. Our novel black/white cartooning procedure was so successful to render comic cuts from a well-known cinema in a resonable time and manual intervention.

Development of an Augmented Reality Puzzle Game Detecting Hand Posture Using HSV Color Space in Real Time (HSV 컬러 영역을 이용한 실시간 손동작 검출 증강현실 퍼즐 게임 개발)

  • Kim, Minhyuk;Kim, Youngsik
    • Journal of Korea Game Society
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    • v.14 no.5
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    • pp.79-86
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    • 2014
  • There have been many trials for development of games using augmented reality. This paper presents a 2D puzzle game system using HSV color space to detect hand posture from an input image by smart device's cameras in real time. The developed game in this paper brings smart devices and the computer vision closer. Also this game can be a new interactive technology utilizing both the mobility of smart devices and the tangible interactivity of virtual reality in education and entertainment environments.

An Efficient Color Edge Detection Using the Mahalanobis Distance

  • Khongkraphan, Kittiya
    • Journal of Information Processing Systems
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    • v.10 no.4
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    • pp.589-601
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    • 2014
  • The performance of edge detection often relies on its ability to correctly determine the dissimilarities of connected pixels. For grayscale images, the dissimilarity of two pixels is estimated by a scalar difference of their intensities and for color images, this is done by using the vector difference (color distance) of the three-color components. The Euclidean distance in the RGB color space typically measures a color distance. However, the RGB space is not suitable for edge detection since its color components do not coincide with the information human perception uses to separate objects from backgrounds. In this paper, we propose a novel method for color edge detection by taking advantage of the HSV color space and the Mahalanobis distance. The HSV space models colors in a manner similar to human perception. The Mahalanobis distance independently considers the hue, saturation, and lightness and gives them different degrees of contribution for the measurement of color distances. Therefore, our method is robust against the change of lightness as compared to previous approaches. Furthermore, we will introduce a noise-resistant technique for determining image gradients. Various experiments on simulated and real-world images show that our approach outperforms several existing methods, especially when the images vary in lightness or are corrupted by noise.

Content-based image retrieval using color (Hue를 이용한 내용기반 검색)

  • Kim Dong-Woo;Chang Un-Dong;Kim Young-Gil;Song Young-Jun
    • Proceedings of the Korea Contents Association Conference
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    • 2005.05a
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    • pp.480-483
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    • 2005
  • This study has proposed a method of content-based image retrieval in order to overcome disadvantages of color histogram. The existing histogram method has a weak point that reduces accuracy because of quantization error, and more. In order to solve this, we convert color information to HSV and quantize Hue factor being net color information and calculate histogram and then use this for retrieval feature that is robust in brightness, movement, and rotation. As a result of experimenting, the method proposed has showed better precision than the existing method.

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An Automatic Object Extraction Method Using Color Features Of Object And Background In Image (영상에서 객체와 배경의 색상 특징을 이용한 자동 객체 추출 기법)

  • Lee, Sung Kap;Park, Young Soo;Lee, Gang Seong;Lee, Jong Yong;Lee, Sang Hun
    • Journal of Digital Convergence
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    • v.11 no.12
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    • pp.459-465
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    • 2013
  • This paper is a study on an object extraction method which using color features of an object and background in the image. A human recognizes an object through the color difference of object and background in the image. So we must to emphasize the color's difference that apply to extraction result in this image. Therefore, we have converted to HSV color images which similar to human visual system from original RGB images, and have created two each other images that applied Median Filter and we merged two Median filtered images. And we have applied the Mean Shift algorithm which a data clustering method for clustering color features. Finally, we have normalized 3 image channels to 1 image channel for binarization process. And we have created object map through the binarization which using average value of whole pixels as a threshold. Then, have extracted major object from original image use that object map.

Software development for the visualization of brain fiber tract by using 24-bit color coding in diffusion tensor image

  • Oh, Jung-Su;Song, In-Chan;Ik hwan Cho;Kim, Jong-Hyo;Chang, Kee-Hyun;Park, Kwang-Suk
    • Proceedings of the KSMRM Conference
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    • 2002.11a
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    • pp.133-133
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    • 2002
  • Purpose: The purpose of paper is to implement software to visualize brain fiber tract using a 24-bit color coding scheme and to test its feasibility. Materials and Methods: MR imaging was performed on GE 1.5 T Signa scanner. For diffusion tensor image, we used a single shot spin-echo EPI sequence with 7 non-colinear pulsed-field gradient directions: (x, y, z):(1,1,0),(-1,1,0),(1,0,1),(-1,0,1),(0,1,1),(0,1,-1) and without diffusion gradient. B-factor was 500 sec/$\textrm{mm}^2$. Acquisition parameters are as follows: TUTE=10000ms/99ms, FOV=240mm, matrix=128${\times}$128, slice thickness/gap=6mm/0mm, total slice number=30. Subjects consisted of 10 normal young volunteers (age:21∼26 yrs, 5 men, 5 women). All DTI images were smoothed with Gaussian kernel with the FWHM of 2 pixels. Color coding schemes for visualization of directional information was as follows. HSV(Hue, Saturation, Value) color system is appropriate for assigning RGB(Red, Green, and Blue) value for every different directions because of its volumetric directional expression. Each of HSV are assigned due to (r,$\theta$,${\Phi}$) in spherical coordinate. HSV calculated by this way can be transformed into RGB color system by general HSV to RGB conversion formula. Symmetry schemes: It is natural to code the antipodal direction to be same color(antipodal symmetry). So even with no symmetry scheme, the antipodal symmetry must be included. With no symmetry scheme, we can assign every different colors for every different orientation.(H =${\Phi}$, S=2$\theta$/$\pi$, V=λw, where λw is anisotropy). But that may assign very discontinuous color even between adjacent yokels. On the other hand, Full symmetry or absolute value scheme includes symmetry for 180$^{\circ}$ rotation about xy-plane of color coordinate (rotational symmetry) and for both hemisphere (mirror symmetry). In absolute value scheme, each of RGB value can be expressed as follows. R=λw|Vx|, G=λw|Vy|, B=λw|Vz|, where (Vx, Vy, Vz) is eigenvector corresponding to the largest eigenvalue of diffusion tensor. With applying full symmetry or absolute value scheme, we can get more continuous color coding at the expense of coding same color for symmetric direction. For better visualization of fiber tract directions, Gamma and brightness correction had done. All of these implementations were done on the IDL 5.4 platform.

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Analysis of Apple Colors and Sugar Contents Using Linear Regression (선형회귀를 이용한 사과의 색상과 당도 분석)

  • Kim, Seon-Jong
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.1
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    • pp.201-207
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    • 2022
  • In this paper, the relationship between RGB, HSV, La*b* colors and sugar content was analyzed using linear regression on apples harvested in the same region. First, as a result of examining the correlation coefficient with sugar content according to each color level, it was found that the (+) region having a positive coefficient and a (-) region having a negative coefficient were separated according to the color level. Also, the correlation coefficient between color and sugar content, represented by the average value, was 0.342 in the La*b* color space, which was higher than the coefficient in the RGB and hsv space. That is, this means that the sugar content is related to the color in the La*b* space. Also, in the complex color composed of regions with high sugar content, it was found to be R2=0.3627, indicating that it is related to sugar content. In all nine color spaces, it was found to be R2=0.3668. In this case, it was found that the coefficients of v and b* had an effect on the sugar content. Due to this, it was possible to confirm the validity of the empirical prediction that the higher the b* representing yellow, the higher the sugar content.

Adaptive Color Shifter for RGB Channel Unbalance in Organic Light Emitting Diode Display (OLED Display의 RGB 채널간 불균형 보정을 위한 Adaptive Color Shifter)

  • Cho, Ho-Sang;Jang, Kyoung-Hoon;Kim, Chang-Hun;Kang, Bong-Soon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.8
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    • pp.1653-1662
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    • 2012
  • Recently, Organic Light Emitting Diode (OLED) that is broadly applied as next generation display has various advantages. However, OLED display causes unbalanced color tone due to the difference of luminance efficiency among luminous elements. In this paper, we propose adaptive color shifter (ACS) to resolve the RGB channel unbalance and to have wide color range of a relatively weak channel using the image processing method. proposed ACS system was simulated using a variety of image. Also, we numerically analyzed using hue histogram, CIE-1931 xyz color space.

Freshness measurement based on HSV color mode (HSV 색상 모형을 기반으로 한 과일 신선도 측정)

  • kwon, Se-hyun;Jo, Su-jang;Hwang, Seung-jin;Hwang, Ho-yeon;Yoo, Ji-yeon;Shin, Sung-Yoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.356-357
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    • 2018
  • 상온에서의 식자재의 시간에 따른 색상 변화 정도를 통해 식자재의 신선도를 파악한다. 식자재 데이터는 임의의 식자재를 선택하여 온도, 습도 등의 외부환경이 동일한 실험환경을 조성한 후 일정 시간 간격으로 식자재 영상을 획득하여 얻는다. 영상 속 식자재의 색상은 기본이 되는 RGB 색상 모델에서 빛에 대하여 강건한 HSV 색상으로 변환 산출하여 변색 정보를 파악한다. 식자재의 기존 색상과 변색 정도를 일련의 관계식으로 산출하며, 산출된 수식을 통하여 영상 속 식자재의 신선도를 산출 추정이 가능하다. 본 논문에서 제안된 기술은 요식업계에서 식자재를 관리할 때 적용하여 식자재를 관리할 수 있다.

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