• Title/Summary/Keyword: HSV Color

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Color-based Face Detection for Alife Robot

  • Feng, Xiongfeng;Kubik, K.Bogunia
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.49.2-49
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    • 2001
  • In this paper, a skin-color model in the HSV space was developed. Based on it, face region can be separated from other parts in a image. Face can be detected by the methods of Template and eye-pair. This realized in our robot.

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The Flame Color Analysis of Color Models for Fire Detection (화재검출을 위한 컬러모델의 화염색상 분석)

  • Lee, Hyun-Sul;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
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    • v.8 no.3
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    • pp.52-57
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    • 2013
  • This paper describes the color comparison analysis of flame in each standard color model in order to propose the optimal color model for image processing based flame detection algorithm. Histogram intersection values were used to analyze the separation characteristics between color of flame and color of non-flame in each standard color model which are RGB, YCbCr, CIE Lab, HSV. Histogram intersection value in each color model and components is evaluated for objective comparison. The analyzed result shows that YCbCr color model is the most suitable for flame detection by average HI value of 0.0575. Among the 12 components of standard color models, each Cb, R, Cr component has respectively HI value of 0.0433, 0.0526, 0.0567 and they have shown the best flame separation characteristics.

Evaluation of the Use of Color Distribution Image Search in Various Setup (칼라 분포정보를 이용한 성능적 이미지 검색 평가)

  • Lee, Yong-Hwan;Ahn, Hyo-Chang;Rhee, Sang-Burm;Park, Jin-Yang
    • Journal of the Korea Computer Industry Society
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    • v.7 no.5
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    • pp.537-544
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    • 2006
  • Image Search is one of the most exciting and fast growing research areas in the filed of multimedia technology. This paper conducts an empirical evaluation of color descriptor that uses the information of color distribution in color images, which is the most basic element for image search. With the experimental results, we observe that in the top 10% of precision, HSV, Daubechies 9/7 and 2 level decomposition have little better than others. Also histogram quadratic metrics outperform the Minkowski form distance metrics in similarity measurements, but spend more than 20 in computational times.

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Object-Tracking System Using Combination of CAMshift and Kalman filter Algorithm (CAMshift 기법과 칼만 필터를 결합한 객체 추적 시스템)

  • Kim, Dae-Young;Park, Jae-Wan;Lee, Chil-Woo
    • Journal of Korea Multimedia Society
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    • v.16 no.5
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    • pp.619-628
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    • 2013
  • In this paper, we describe a strongly improved tracking method using combination of CAMshift and Kalman filter algorithm. CAMshift algorithm doesn't consider the object's moving direction and velocity information when it set the search windows for tracking. However if Kalman filter is combined with CAMshift for setting the search window, it can accurately predict the object's location with the object's present location and velocity information. By using this prediction before CAMshift algorithm, we can track fast moving objects successfully. Also in this research, we show better tracking results than conventional approaches which make use of single color information by using both color information of HSV and YCrCb simultaneously. This modified approach obtains more robust color segmentation than others using single color information.

Detection of corrosion on steel plate by using Image Segmentation Method (영상분할법을 이용한 강판상의 부식 감지)

  • Kim, Beomsoo;Kim, Yeonwon;Yang, Jeonghyeon
    • Journal of the Korean institute of surface engineering
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    • v.54 no.2
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    • pp.84-89
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    • 2021
  • The visual inspection method is widely used for corrosion damage analysis of steel plate due to the cost-efficient, fast and reasonably accurate results. However, visual inspection of corrosion deteriorated degree has a problem that the reliability of results differs depending on the inspector's individual knowledge and experience. In this study, we evaluated the degree of corrosion from a given image by using image segmentation method based on the grabcut and HSV(Hue, Saturation, Value) color image processing techniques for the development of an automatic inspection tool. The code written in Python based OpenCV-python libraries was used to categorize the images.

A Study on Automatic Detection of Speed Bump by using Mathematical Morphology Image Filters while Driving (수학적 형태학 처리를 통한 주행 중 과속 방지턱 자동 탐지 방안)

  • Joo, Yong Jin;Hahm, Chang Hahk
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.3
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    • pp.55-62
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    • 2013
  • This paper aims to detect Speed Bump by using Omni-directional Camera and to suggest Real-time update scheme of Speed Bump through Vision Based Approach. In order to detect Speed Bump from sequence of camera images, noise should be removed as well as spot estimated as shape and pattern for speed bump should be detected first. Now that speed bump has a regular form of white and yellow area, we extracted speed bump on the road by applying erosion and dilation morphological operations and by using the HSV color model. By collecting huge panoramic images from the camera, we are able to detect the target object and to calculate the distance through GPS log data. Last but not least, we evaluated accuracy of obtained result and detection algorithm by implementing SLAMS (Simultaneous Localization and Mapping system).

Color Image Compensation Method using Advanced Image Formation Model and Adaptive Filter (개선된 영상생성 모델과 적응적 필터를 이용한 칼라 영상 보정방법)

  • Choi, Ho-Hyung;Yun, Byoung-Ju
    • The Journal of the Korea Contents Association
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    • v.9 no.12
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    • pp.10-18
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    • 2009
  • Color rendition method is necessary for improving the low contrast images which are achieved by PDA, mobile phone camera or PC camera. There are some methods for color rendition. However, after correcting the color, image quality degradations, such as graying-out, halo-artifact and color noise, may occur. In order to overcome these problems, this paper proposes a retinex-based color rendition method. The proposed method uses the HSV color coordinate system to avoid the graying-out, and the advanced image formation model to reduce the halo-artifact in which the image is divided into three components as the global illumination, the local illumination, and reflectance. The experiment results show that the proposed method yields better performance of color correction over the conveniently method.

Automatic Color Recognition System for Stockigt Sizing Test (I) - Bias of Stockigt sizing test based on observer's subjectiveness - (스테키히트 시험용 자동 발색 인지 시스템 개발을 위한 기초연구(I) - Stockigt 사이즈도 시험법에 영향을 주는 요인 분석 -)

  • 김재옥;김철환;박종열
    • Journal of Korea Technical Association of The Pulp and Paper Industry
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    • v.36 no.1
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    • pp.1-8
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    • 2004
  • One of the most frequently used method for measurement of the degree of sizing (viz., hydrophobicity) is the Stockigt test. However, the Stockigt test was influenced by various factors such as dropping height, dropping amount, dropping speed and viewing angle. The resultant data of the sizing degree on the same specimen also varied according to different testers. Thus, the Stockigt test should be modified to be regarded as a highly reliable and reproducible standard method. For modifying the Stockigt test, it was required to quantify red coloration by reaction between 1% ferric chloride and 2% ammonium thiocyante during Stockigt testing. The cameras capturing the serial images during the red coloration process were the CMOS (Complementary Metal Oxide Semiconductor)-type and CCD (Charge Coupled Device)-type cameras. For measurement based on KS M 7025, the CCD-type camera must be used due to its high resolution, and on the other hand, for measurement based on Tappi Useful Method 429, the CMOS-type camera may be used owing to its low resolution. It was needed to covert the RGB values of a droplet image into HSV(Hue, Saturation, and Value) values because the human eyes are much closer to HSV than RGB. Among HSV values, the Hue value was accepted as the most reliable index consistent with the red coloration process by excluding the surrounding conditions such as light, tester's movement etc.

Implementation of Image Retrieval System using Complex Image Features (복합적인 영상 특성을 이용한 영상 검색 시스템 구현)

  • 송석진;남기곤
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.8
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    • pp.1358-1364
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    • 2002
  • Presently, Multimedia data are increasing suddenly in broadcasting and internet fields. For retrieval of still images in multimedia database, content-based image retrieval system is implemented in this paper that user can retrieve similar objects from image database after choosing a wanted query region of object. As to extract color features from query image, we transform color to HSV with proposed method that similarity is obtained it through histogram intersection with database images after making histogram. Also, query image is transformed to gray image and induced to wavelet transformation by which spatial gray distribution and texture features are extracted using banded autocorrelogram and GLCM before having similarity values. And final similarity values is determined by adding two similarity values. In that, weight value is applied to each similarity value. We make up for defects by taking color image features but also gray image features from query image. Elevations of recall and precision are verified in experiment results.

Image Retrieval Using Combination of Color and Multiresolution Texture Features (칼라 및 다해상도 질감 특징 결합에 의한 영상검색)

  • Chun Young-deok;Sung Joong-ki;Kim Nam-chul
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.9C
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    • pp.930-938
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    • 2005
  • We propose a content-based image retrieval(CBIR) method based on an efncient combination of a color feature and multiresolution texture features. As a color feature, a HSV autocorrelograrn is chosen which is blown to measure spatial correlation of colors well. As texture features, BDIP and BVLC moments are chosen which is hewn to measure local intensity variations well and measure local texture smoothness well, respectively. The texture features are obtained in a wavelet pyramid of the luminance component of a color image. The extracted features are combined for efficient similarity computation by the normalization depending on their dimensions and standard deviation vectors. Experimental results show that the proposed method yielded average $8\%\;and\;11\%$ better performance in precision vs. recall than the method using BDIPBVLC moments and the method using color autocorrelograrn, respectively and yielded at least $10\%$ better performance than the methods using wavelet moments, CSD, color histogram. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.