• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.15-18
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• 2003

This paper proposes a color matching 3D look-up table simplifying the complex color matching procedure between a monitor and a mobile display device. In order to perform color matching, it is necessary to process color of image in the device independent color space like CIEXYZ or CIELAB. We improved the S-curve model to have smaller characterization error than tolerance error. Also, as a result of the experiments, we concluded that the color matching look-up table with 64(4$\times$4$\times$4) is the smallest size allowing characterization error to be acceptable.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1157-1160
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• 2005

The denoising and reconstruction of color images are increasingly studied in the field of computer vision and image processing. Especially, the denoising and reconstruction of color face images are more difficult than those of natural images because of the structural characteristics of human faces as well as the subtleties of color interactions. In this paper, we propose a denoising method based on PCA reconstruction for removing complex color noises on human faces, which is not easy to remove by using vectorial color filters. The proposed method is composed of the following five steps; training of canonical eigenface space using PCA, automatic extracting of face features using active appearance model, relighing of reconstructed color image using bilateral filter, extraction of noise regions using the variance of training data, and reconstruction using partial information of input images (except the noise regions) and blending of the reconstructed image with the original image. Experimental results show that the proposed denosing method efficiently removes complex color noises on input face images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.83-92
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• 2009

In this paper, an extended snake algorithm using color variance energy is proposed for segmenting an interest object in color image. General snake algorithm makes use of energy in image to segment images into a interesting area and background. There are many kinds of energy that can be used by the snake algorithm. The efficiency of the snake algorithm is depend on what kind of energy is used. A general snake algorithm based on active contour model uses the intensity value as an image energy that can be implemented and analyzed easily. But it is sensitive to noises because the image gradient uses a differential operator to get its image energy. And it is difficult for the general snake algorithm to be applied on the complex image background. Therefore, the proposed snake algorithm efficiently segment an interest object on the color image by adding a color variance of the segmented area to the image energy. This paper executed various experiments to segment an interest object on color images with simple or complex background for verifying the performance of the proposed extended snake algorithm. It shows improved accuracy performance about 12.42 %.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.137-144
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• 2017

Face detection is still a challenging task under severe face pose variations in complex background. This paper proposes an effective algorithm which can detect single or multiple faces based on skin color detection and depth information. We introduce Gaussian mixture model(GMM) for skin color detection in a color image. The depth information is from three dimensional depth sensor of Kinect V2 device, and is useful in segmenting a human body from the background. Then, a labeling process successfully removes non-face region using several features. Experimental results show that the proposed face detection algorithm can provide robust detection performance even under variable conditions and complex background.

• Bulletin of the Korean Chemical Society
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• v.21 no.9
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• pp.923-928
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• 2000

[FeIII(BBA)DBC]ClO4 as a new functional model for catechol dioxygenases has been synthesized, where BBA is a bis(benzimidazolyl-2-methyl)amine and DBC is a 3,5-di-tert-butylcatecholate dianion.The BBA complex has a structuralfeature that iron cent er has a five-coordinate geometry similar to that of catechol dioxygenase-substrate complex.The BBA complex exhibits strong absorptionbands at 560 and 820 nm in CH3CN which are assigned to catecholate to Fe(III) charge transfer transitions. It also exhibits EPR signals at g = 9.3 and 4.3 which are typical values for the high-spin FeIII (S = 5/2) complex with rhombicsymmetry. Interestingly, the BBA complex reacts with O2 within an hour to afford intradiol cleavage (35%) and extradiol cleavage (60%) products. Surprisingly, a green color intermediate is observed during the oxygenation process of the BBA com-plex in CH3CN. This green intermediate shows a broad isotropic EPR signal at g = 2.0. Based on the variable temperature EPR study, this isotropic signalmight be originated from the [Fe(III)-peroxo-catecholate] species havinglow-spin FeIII center, not from the simple organic radical. Consequently,it allows O2 to bind to iron cen-ter forming the Fe(III)-superoxide species that converts to the Fe(III)-peroxide intermediate. These present data can lead us tosuggest that the oxygen activation mechanism take place for the oxidative cleavingcatechols of the five-coordinate model systems for catechol dioxygenases.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.33-41
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• 2004

This paper proposes a color matching 3D look-up table simplifying the complex color matching procedure between a monitor and a mobile display device. In other to perform color matching, it is necessary to process color of image in the device independent color space like CIEXYZ or CIELAB. To obtain the data of the device independent color space from that of the device dependent RGB color space, we must perform display characterizations. LCD characterization error using S-curve model is larger than tolerance error since LCD is more nonlinear than CRT. This paper improves the S-curve model to have smaller characterization error than tolerance error using the electro-optical transfer functions of X, Y, and Z value. We obtained images having higher color fidelity on mobile display devices through color matching experiments between monitor and mobile display devices. As a result of this experiments, we concluded that the color matching look-up table with 64(4${\times}$4${\times}$4) is the smallest size allowing characterization error to be acceptable.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.434-442
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• 2006

This paper proposes a color-matching 3D look-up table that simplifies the complex color-matching procedure between a monitor and a mobile display device, where the image colors are processed in a device-independent color space, such as CIEXYZ or CIELAB, and gamut mapping performed to compensate the gamut difference. The transform from a device-dependent RGB color space to a device-independent color space is implemented by performing display characterization. The mobile LCD characterization error using the S-curve model is larger than the tolerance error since the mobile LCD has the channel-chromaticity-inconstancy and channel-dependence characteristics. In this paper we reduced the characterization error using the electro-optical transfer functions of X, Y, and Z value for R, G, B, C, M, Y, K components. Experimental results demonstrated that 64 ($4{\times}4{\times}4$) was the smallest size of color-matching look-up table that could produce an image with an acceptable reproduction error, based on a comparison of color-matched images resulting from the proposed color-matching look-up table and complex step-by-step color-matching procedures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2400-2419
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• 2014

Pre-segmented pixels can reduce the difficulty of segmentation and promote the segmentation performance. This paper proposes a novel segmentation method based on merging texture superpixels by computing inner similarity. Firstly, we design a set of Gabor filters to compute the amplitude responses of original image and compute the texture map by a salience model. Secondly, we employ the simple clustering to extract superpixles by affinity of color, coordinates and texture map. Then, we design a normalized histograms descriptor for superpixels integrated color and texture information of inner pixels. To obtain the final segmentation result, all adjacent superpixels are merged by the homogeneity comparison of normalized color-texture features until the stop criteria is satisfied. The experiments are conducted on natural scene images and synthesis texture images demonstrate that the proposed segmentation algorithm can achieve ideal segmentation on complex texture regions.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.5
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• pp.1-11
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• 2007

As the availability of an image information has been significantly increasing, necessity of system that can manage an image information is increasing. Accordingly, we proposed the region-based content retrieval(CBIR) algorithm based on an efficient combination of an image segmentation, an image texture, a color feature and an image's shape and position information. As a color feature, a HSI color histogram is chosen which is known to measure spatial of colors well. We used active contour and CWT(complex wavelet transform) to perform an image segmentation and extracting an image texture. And shape and position information are obtained using Hu invariant moments in the luminance of HSI model. For efficient similarity computation, the extracted features(color histogram, Hu invariant moments, and complex wavelet transform) are combined and then precision and recall are measured. As a experimental result using DB that was supported by www.freefoto.com. the proposed image retrieval engine have 94.8% precision, 82.7% recall and can apply successfully image retrieval system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.740-745
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• 2003

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks suck as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. Snake is designed no the basis of snake energies. Segmenting and tracking can be executed successfully by energy minimization. In this research, two new paradigms for segmentation and tracking are suggested. First, because the conventional method uses only intensity information, it is difficult to separate an object from its complex background. Therefore, a new energy and design schemes should be proposed for the better segmentation of objects. Second, conventional snake can be applied in situations where the change between images is small. If a fast moving object exists in successive images, conventional snake will not operate well because the moving object may have large differences in its position or shape, between successive images. Snakes's nodes may also fall into the local minima in their motion to the new positions of the target object in the succeeding image. For robust tracking, the condensation algorithm was adopted to control the parameters of the proposed snake model called "adaptive color snake model(SCSM)". The effectiveness of the ACSM is verified by appropriate simulations and experiments.