• Journal of Embryo Transfer
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• v.28 no.3
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• pp.215-222
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• 2013

Bovine coat color is decided by the melanocortin receptor 1 (MC1R) genotype mutation and melanogenesis. Specially, in the various cattle breeds, dominant black coat color is expressed by dominant genotype of $E^D$, red or brown is expressed in the frame shift mutation of recessive homozygous e by base pair deletion and wild type of $E^+$ is expressed in various coat colors. However, not very well known about the effected of MC1R genotype mutation on the coat color through family lines in KBC. Therefore, this study were to investigate effect of MC1R genotype mutation on the coat color, and to suggest mating breed system in accordance with of MC1R genotype for increased on brindle coat color appearance. Parents (sire 2 heads and dam 3 heads) and offspring (total : 54 heads) from crossbreeding in KBC family line with the MC1R genotype and phenotype records were selected as experimental animals. The relationship between melanocortin 1 receptor (MC1R) genotypes expression verified by PCR-RFLP, and brindle coat color appearance to the family line of the cross mating breed from MC1R genotype pattern was determined. As a result, 4MC1R genetic variations, $E^+/E^+$ (sire 1), $E^+/e$ (sire 2 and dam 3), $E^+/e$ with 4 bands of 174, 207 and 328 bp (dam 1) and $E^+/e$ with 3 bands of 174, 207, 328 and 535 bp (dam 2) from parents (sire and dam) of KBC. However, 3 genetic variations, e/e (24%), $E^+/E^+$ (22%) and $E^+/e$ (56%) were identified in offspring. Also, brindle coat color expressrated was the e/e with the 0%, $E^+/E^+$ with 67% and $E^+/e$ with 77% from MC1R genotype in offspring on the cross mating of KBC. Furthermore, when the sire had $E^+/e$ genotype and the dam had $E^+/E^+$ with the 3 bands or $E^+/e$ genotype, and both had whole body-brindle coat color, 62% of the offspring had whole body-brindle coat color. Therefore, the seresults, the mating system from MC1R genotype patterns of the sires ($E^+/e$) and dams ($E^+/E^+$ with the 3 bands or $E^+/e$) with brindle coat color may have the highest whole body-brindle coat color expression in their offspring.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.135-135
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• 2001

In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks that have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, we have a global search for entire image and then have tracking the object through local search when the object is recognized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4534-4555
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• 2015

We propose a robust object cataloging method using multiple locally distinct heterogeneous features for aiding image retrieval. Due to challenges such as variations in object size, orientation, illumination etc. object recognition is extraordinarily challenging problem. In these circumstances, we adapt local interest point detection method which locates prototypical local components in object imageries. In each local component, we exploit heterogeneous features such as gradient-weighted orientation histogram, sum of wavelet responses, histograms using different color spaces etc. and combine these features together to describe each component divergently. A global signature is formed by adapting the concept of bag of feature model which counts frequencies of its local components with respect to words in a dictionary. The proposed method demonstrates its excellence in classifying objects in various complex backgrounds. Our proposed local feature shows classification accuracy of 98% while SURF,SIFT, BRISK and FREAK get 81%, 88%, 84% and 87% respectively.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2197-2207
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• 1997

In this paper, we propose a video data segmentation method using edge and color distribution of video frames and also develop a video browser by using the proposed algorithm. To segment a video, we use a 644-bin HSV color histogram and the edge information which generated with automatic threshold method. We consider scene's characteristics by using positions and colo distributions of object in each frame. We develop a hierarchical and a shot-based browser for video browsing. We also show that our proposed method is less sensitive to light effects and more robust to motion effects than previous ones like a histogram-based method by testing with various video data.

• The KIPS Transactions:PartB
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• v.15B no.2
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• pp.113-122
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• 2008

While there are about 1 million color vision deficiencies in Korea, an assistive technology to digital contents of broadcasting and web for them remains scarce. In this study, we developed a generation method of the ICC profile to correct a graphic digital content adapted to various color perception characteristics of CVD by tuning the correction rules of the ICC profile by themselves. We tested the performance of the ICC profile to apply 10 Ishihara plates to the participants, 1 protanomaly, 1 protanomaly and deuteranomaly and 2 deuteranomaly. We used the color range information to build correction rules. Results of the test show that they passed Ishihara test by 97.5% success rate, compared to 20% success rate without it. The average time for them to spend to tune the customized ICC profile was about 13 minute without any diagnosis of specialist, any special instrument.

• Journal of Korea Multimedia Society
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• v.8 no.5
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• pp.633-640
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• 2005

In this paper, we propose an adaptive face region extraction algorithm based on skin color information. It consists oi the extraction of face candidate region and projection step. In the step of face candidate region extraction, we extract the pixels which are regarded as the candidate skin color pixels by using the given range. Then, the ratio between the total pixels and the extracted pixels is calculated. According to the ratio, we adaptively decide the range of the skin color and extract face candidate region. In the projection step, we project the extracted face candidate region into vertical direction to estimate the width of the face. Then the redundant parts are efficiently removed by using the estimated face width. And the extracted face width information is used at the horizontal projection step to extract the height of the face. From the experiment results for the various images, the proposed algorithm shows more accurate results than the conventional algorithm.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.66-75
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• 2010

We proposed an occupant sensing system using single video camera and ultrasonic sensor for the advanced airbag. To detect the occupant form and the face position in real-time, we used the skin color and motion information. We made the candidate face block image using the threshold value of the color difference signal corresponding to skin color and difference value of current image and previous image of luminance signal to gel motion information. And then it detects the face by the morphology and the labeling. In case of night without color and luminance information, it detects the face by using the threshold value of the luminance signal get by infra-red LED instead of the color difference signal. To evaluate the performance of the proposed occupant detection system, it performed various experiments through the setting of the IEEE camera, ultrasonic sensor, and infra-red LED in vehicle jig.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.63-73
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• 2009

This paper presents a vehicle detection method that uses convolution matching method based on a simple color information. An input image is expressed as 8 oriented color expression(Red, Green, Blue, White, Black, Cyan, Yellow, Magenta) considering an orientation of a pixel color vector. It makes the image very reliable and strong against changes of illumination condition or environment. This paper divides the vehicle detection into a hypothesis generation step and a hypothesis verification step. In the hypothesis generation step, the vehicle candidate region is found by vertical edge and shadow. In the hypothesis verification step, the convolution matching and the complexity of image edge are used to detect real vehicles. It is proved that the proposed method has the fast and high detection rate on various experiments where the illumination source and environment are changed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.1-10
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• 2010

There have been studied with activity about color standard due to extention of digital contents' application area. Therefore the studies in relation to the standard are needed to represent image's feature as color. Also the methods to extract color's feature to be apt to various application are needed. In this paper, we set the base color as 50 colors from Munsell color system, get the color histogram to show the characteristics of colors's distribution of a image, and propose the method to extract representative colors from the histogram. Firstly, we convert a input image of RGB color space to a image of HSI color space and split the image into hue area and non-hue area. To split hue area and non-hue area, we use a fixed threshold and a perception-function of color area function to reflect the subjective vision of human-being. We compute histograms from each area and then make a total histogram from the histogram of hue area and the histogram of hue area, and extract the representative colors from the histogram. To evaluate the proposed method, we made 18 test images, applied conventional methods and proposed method to them Also the methods are applied to public images and the results are analyzed. The proposed method represents well the characteristics of the colors' distribution of images and piles up colors' frequency to representative colors. Therefore the representative colors can be applied to various applications

• Science of Emotion and Sensibility
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• v.23 no.3
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• pp.63-78
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• 2020

It is crucial to process not only social cognitive information but also various emotional information for appropriate social interaction in everyday life. The processing of emotions embedded in social stimuli is affected by various context and external factors and the features of their own. Emotion discrimination tasks using point-light biological motion were conducted in this study to understand the factors influencing emotion processing and their effects. A target biological motion with angry or happy emotion was presented in the first task in red, green, white, or yellow color. A white angry, happy, or neutral "cue" biological motion was displayed simultaneously. Participants judged the emotion of the target relative to the cue stimulus by comparing the target with the cue. The second task used only emotionally neutral stimuli to find effect by the color itself. The results indicated an association between the specific color of the target and emotion. Red facilitated processing anger, whereas green appeared to facilitate happy emotion. The discrimination accuracy was high when the emotions of the cue and the target were identical in general, but the combination of red color and anger yielded different results compared with the rest of the conditions. Some illusory emotional responses associated with the target colors were observed in the second task. We could observe the effects of external factors in this study, affecting the emotional processing using biological motion rather than conventional face stimuli. Possible follow-up studies and clinical research were discussed.