• 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.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.2
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• pp.16-22
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• 2010

This paper proposes the real-time moving object tracking system UAV using color information. Case of object tracking, it have studied to recognizing the moving object or moving multiple objects on the fixed camera. And it has recognized the object in the complex background environment. But, this paper implements the moving object tracking system using the pan/tilt function of the camera after the object's region extraction. To do this tracking system, firstly, it detects the moving object of RGB/HSI color model and obtains the object coordination in acquired image using the compact boundary box. Secondly, the camera origin coordination aligns to object's top&left coordination in compact boundary box. And it tracks the moving object using the pan/tilt function of camera. It is implemented by the Labview 8.6 and NI Vision Builder AI of National Instrument co. It shows the good performance of camera trace in laboratory environment.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.562-570
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• 2012

This paper proposes a robust object tracking algorithm using object features and on-line learning based particle filter for mobile robots. Mobile robots with a side-view camera have problems as camera jitter, illumination change, object shape variation and occlusion in variety environments. In order to overcome these problems, color histogram and HOG descriptor are fused for efficient representation of an object. Particle filter is used for robust object tracking with on-line learning method IPCA in non-linear environment. The validity of the proposed algorithm is revealed via experiments with DBs acquired in variety environment. The experiments show that the accuracy performance of particle filter using combined color and shape information associated with online learning (92.4 %) is more robust than that of particle filter using only color information (71.1 %) or particle filter using shape and color information without on-line learning (90.3 %).

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.1
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• pp.25-33
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• 2000

In recent year, many imaging systems have been developed, and it became increasingly important to exchange image data through the computer network. Therefore, it is required to reproduce color image independently on each imaging device. However, even if the image are same, perceived color is not always same under different viewing conditions. On the other hand, even if the image are different, we want to perceive same color under different viewing conditions. Therefore we must know the spectral reflectance information of object. We measured many reflectance human skin can be estimate using only three principal component. For Munsell color patches, five principle components were necessary to estimate the reflectance spectra. For that purpose, we have developed color image acquisition system that is composed of five band filters and CCD camera. Improved spectral reflectance of object is predicted by five band images taken by color image acquisition system and then we take account of camera's noise and component of object image for predicting accurate spectral reflectance of object. In the results, we confirmed that color difference and MSE(Mean Square Error) between measured and predicted spectral reflectance of object decreased into 0.0071 and 7.72 respectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.39-46
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• 2006

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and intelligent space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in intelligent space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.1
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• pp.47-58
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• 1996

An object color can be seen differently under the various outer illuminants. However, human visual system has color constnacy that the object color can be seen constantly under the different outer illuminants. When the viewer watches TV under specific that the object color can be seen constantly under the different outer illuminants. When the viewer bathes TV under specific outer illuminants, he perceives distortes color due to the emitting specturm of outer illuminants as well as the radiation of CPT itself. Namely, when the outer illuminants such as fluorescent and incandescent lamps incident on CPT, brightness, saturation, hue, itself. Namely, when the outer iluminants such as fluorescent and incandescent lamps incident on CPT, brightness, saturation, hue, and contrast on color pictures are changend, he perceives distortedcolr fromthe original color. In this paper color enhancement algorithm based on light intensity and outer light decision funtion using RGB sensor was proposed. The implemented TV of proposed algorithm has higher visual quality at the view point of human visual system and more vivid than that ofcoventional color TV.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.2
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• pp.1-8
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• 2003

This paper proposes an object-based image retrieval technique based on the dominant color pair information. Most of existing methods for content based retrieval extract the features from an image as a whole, instead of an object of interest. As a result, the retrieval performance tends to degrade due to the background colors. This paper proposes an object based retrieval scheme, in which an object of interest is used as a query and the similarity is measured on candidate regions of DB images where the object may exist. From the segmented image, the dominant color pair information between adjacent regions is used for selecting candidate regions. The similarity between the query image and DB image is measured by using the color correlogram technique. The dominant color pair information is robust against translation, rotation, and scaling. Experimental results show that the performance of the proposed method has been improved by reducing the errors caused by background colors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.727-731
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• 2005

We introduce a method of color-coded illumination that is simple and fast. The purpose of this study is the real-time shape measurement of three-dimensional object by using color-coded information. The object is illuminated by a prism color spectrum. A color spectrum of a white-light source is imaged onto the object by illumination from one certain direction. The object is observed by a color CCD camera from a direction of observation, which is different from the direction of illumination. It can be evaluated by the red, blue, green using a inherence colors of hue value are good point.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.557-560
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• 2005

The color of objects varies with changes in illuminant color and viewing conditions. As a consequence, color boundaries are influenced by a large variety of imaging variables such as shadows, highlights, illumination, and material changes. Therefore, invariant color models are useful for a large number of applications such as object recognitions, detections, and segmentations. In this paper, we propose invariant color models. These color models are independent of the object geometry, object pose, and illumination. From these color models, color invariant edges are derived. To show the validity of the proposed invariant color models, some examples are given.

• Journal of the Korean Graphic Arts Communication Society
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• v.16 no.3
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• pp.97-108
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• 1998

Spectral reflectance of the object should be measured to predict the color of object under various illuminants. The spectral reflectance can be represented in a multi-dimension space. Generally the information of inputed image by digital camera and color scanner is represented with 3-dimension color signals such as RGB. In other to predict the color of inputed image under any illuminant, we should be estimated spectral reflectance of the object. In this paper, we described the method to predict spectral reflectance by einenvector using the skin color of printed image, confirmed availability and propriety through experiment. we estimated spectral reflectance of skin color taken by RGB color signals and than reproduced skin color according to various illuminants on CRT.