• Title/Summary/Keyword: RGB color information

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Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

  • Zhou, Zibo;Peng, Dongliang;Gao, Fumeng;Leng, Lu
    • Journal of Multimedia Information System
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    • v.6 no.2
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    • pp.99-106
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    • 2019
  • In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

Crop-row Detection by Color Line Sensor

  • Ha, S.ta;T.Kobaysahi;K.Sakai
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1993.10a
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    • pp.353-362
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    • 1993
  • The purpose of this study is to develop a crop-row detector which can be applied to an automatic row following control for cultivators or thinning machines. In this report, a possibility of new crop-row detecting method was discussed. This detecting method consists of two principal means. One is the hardware means to convert the two dimensional crop-row vision to the compacted one dimensional information. The conversion is achieved by a color line sensor and a rotating mirror. In order to extract crop-row , R and G signals of RGB color system are used. The locations of two different points on the target row are detected by this means. Another is the software means to estimate the offset value and the heading angle between the detector and the target row which can be assumed as a straight line. As a result of discussion, it was concluded that this detecting method would be accurate enough for practical use.

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Color correction of tile color input device using the Neural Network (신경망을 이용한 칼라 입력장치의 칼라 보정)

  • Eum, Kyoung-Bae;Ahn, Chang-Sun
    • Journal of The Korean Association of Information Education
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    • v.3 no.1
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    • pp.134-142
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    • 1999
  • The demand for recognizing the color as well as the object shape is increasing to use the detailed information, because-the expense of color input/output devices become cheap. The research on the color correction should be researched for the exact color presentation and color reproduction of color input/output systems. In this paper, we researched on the color correction of color scanner. The characterization of color scanner is a two step process of gray-balancing and color transformation. The decoupling of the gray-balancing from the color transformation enables the portability of the scanner characterization. We used the least square methods for the line fitting and the Neural Network for the storage space and computation speed. The output of Neural Network is similar to the target value in three-dimensional tristimulus space. The proposed color correction method can be used for all scanners of a manufacturer's model because of the portability.

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Face Detection based on Multi-Channel Skin-Color Model (다채널 피부색 모델에 기반한 얼굴 영역 검출)

  • 김영권;고재필;변혜란
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.433-435
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    • 2001
  • 얼굴 인식분야에서 실시간 얼굴검출에 대한 관심이 높아짐에 따라 피부색컬러 모델을 통한 얼굴영역검출에 대한 연구가 활발히 진행되고 있다. 그러나, 기존의 피부색 모델은 밝기 정보를 제거한 단일 채널의 색상모델이 대부분이다. 이에 본 논문에서는 얼굴피부색을 보다 효과적으로 모델링하기 위하여, 피부색 특성을 고려하여, 밝기 성분을 제거한 RGB 컬러를 모두 사용하는 H, Cb, Cg의 다채널 피부색 모델을 제시한다. 또한, 색상정보에서 사용하지 않은 밝기 정보는 영상 분할을 통해 사용한다. 제안하는 피부색 모델을 통한 얼굴영역 추출 과정을 보인다.

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Development of a PC-based 3-D Seismic Visualization Software (PC 기반의 3차원 탄성파 자료 시각화 소프트웨어 개발 연구)

  • Kim, Hyeon-Gyu;Lee, Doo-Sung
    • Geophysics and Geophysical Exploration
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    • v.6 no.1
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    • pp.35-39
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    • 2003
  • A software to visualize and analyse 3-D seismic data is developed using OpenGL, one of the most popular 3-D graphic library, under the PC and Windows platform. The software can visualize the data as volume and slices, whose color distribution is specified by a special dialog box that can pick a color in RGB or HSV format. The dialog box can also designate opacity values so that several 3-D objects can be displayed superimposed each other. Horizon picking is implemented very easily with this software thanks to the guided picking method. The picked points from a horizon will compose a set of points, mesh, and a surface, which can be viewed and analysed in three dimensions.

Analysis of the spectroscopic characteristics of Ground color images using a digital camera (디지털 카메라를 활용한 컬러 지상영상의 분광학적 특성 분석)

  • Ko, In-Chul;Seo, Su-Young
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2010.06a
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    • pp.137-144
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    • 2010
  • Ground digital image data obtained by using DSLR camera can be used to the ground photogrammetry and spatial modeling. Intensity of each pixel in digital video images is the most important parameter to generate digital image. Therefore, it is needed to estimate the parameters and spectral characteristics of digital cameras in order to take more definite intensity data. In this study, using the Sony DSC-F828 DSLR camera, seven digital images are obtained by the continuous shooting. (frame rate, 0.38 seconds). And then extract the value of the intensity from RGB band of each digital color photographs to confirm difference of intensity between frames. The purpose of this study is to confirm spectral characteristics and changes and to estimate correlation through the analysis of statistical in each pixel of R, G, B band.

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Estimation of chlorophyll and pheophytin contents of rice (Oryza sativa L.) leaf in seedling bed using CIE chromaticity diagram

  • Kim, Tae Sung;Ham, Hyun Don;Lee, Mi Hyun;Park, Ki Bae;Yoo, Sung Yung;Kim, Tae Wan
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2017.06a
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    • pp.243-243
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    • 2017
  • Leaf colors of rice can be used to identify stress level due to its adaptation to environmental change. For most leaves green-related colors are sourced from chlorophyll a and b. For most leaves green-related colors are consisted of chlorophyll a and b. Chlorophyll concentration is normally measured using a spectrophotometer in laboratory. In some remote observation fields, it is impossible to collect the leaves, preserve them, and bring them to laboratory to measure their chlorophyll content. The measurement of chlorophyll content is observed through its color. Using CIE chromaticity diagram leaf color information in RGB is transformed into wavelength (in nm). Pheophytin contents were also analyzed in 95% ethanol extracts. In the process of leaf development of rice young seedling, both pigments were compared. Leaf samples from different rice seedling bed is taken, their colors and RGB values are recorded using Photoshop Image Analysis. SPAD-502 values were also measured. The chlorophyll and Pheophytin contents were fully estimated by ${\rightthreetimes}_{avg}$ on CIE chromaticity diagram.

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Edge Extraction Method Based on Color Image Model (컬러 영상 모델에 기반한 에지 추출기법)

  • Kim Tae-Eun
    • Journal of Digital Contents Society
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    • v.4 no.1
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    • pp.11-21
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    • 2003
  • In computer vision, the goal of stereopsis is to determine the surface structure of real world form two or more perspective views of scene. It is similar to human visual system. We can avoid obstacles, recognize objects, and manipulate machine using three-dimensional information. Until recently, only gray-level images have been used as input to computation for depth determination, but the availability of color can further enhance the performance of computational stereopsis. There are many models to provide efficient color system. The simplest model, RGB model treats color as if it were composed of separate entities. Each color channel is processed individually by the same stereopsis module as used in the gray-level model. His Model decouples intensity component from color information. So it can deal with color properties without defect intensity information. Opponent color model is based on human visual system. In this model, the red-green-blue colors are combined into three opponent channels before further processing.

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Recognition of Traffic Signs using Wavelet Transform and Shape Information (웨이블릿 변환과 형태 정보를 이용한 교통 표지판 인식)

  • 오준택;곽현욱;김욱현
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.125-134
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    • 2004
  • This paper proposes a method for recognition of traffic signs using wavelet transform and shape information from the segmented traffic sign regions. It first segments traffic sign candidate regions by connected component algorithm from binary images, obtained by utilizing the RGB color ratio of each pixel in the image, and then extracts actual traffic sign regions based on their symmetries on X- and Y-axes. In the recognition stage, it utilizes shape information including moment edge correlogram and the number of crossings which concentric circular patterns from region center intersects with frequency information extracted by wavelet transform It finally performs recognition by measuring similarity with the templates in the database. The experimental results show the validity of the proposed method from geometric transformations and environmental factors.

Dense RGB-D Map-Based Human Tracking and Activity Recognition using Skin Joints Features and Self-Organizing Map

  • Farooq, Adnan;Jalal, Ahmad;Kamal, Shaharyar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.5
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    • pp.1856-1869
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    • 2015
  • This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.