• Journal of Physiology & Pathology in Korean Medicine
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• v.27 no.5
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• pp.683-687
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• 2013

Evacuation disorder(ED) is frequently observed in the elderly people. In this study, we investigated the tongue color properties in the elderly. 327 subjects were participated in this study and classified into normal group (n=95) and ED group (n=23) by two Korean Oriental Medicine doctors. The tongue images were acquired by using computerized tongue diagnosis system, and its color were linearly corrected base on CIE $L^*a^*b^*$ values of 12 color samples. The tongue region was segmented from acquired image and divided into two regions along the vertical direction. In order to estimate color properties of the tongue, a color histogram was calculated for the root region based on the CIE $L^*$ and $a^*$ values, and differences of color histogram values between normal and ED groups were computed based on the Mann-Whitney U test. As results, pixels corresponding to typical colors of the pale tongue and thin tongue coating were significantly more distributed in ED than those in normal group(p<0.05). The tongue color of the root region in ED was revealed to be different from those in healthy subjects.

• International Journal of Advanced Culture Technology
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• v.3 no.2
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• pp.161-170
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• 2015

Mean separated histogram equalization in order to preserve the original mean brightness has been proposed. To provide the minimum mean brightness error after the histogram modification, the input image's histogram is successively divided by the factor of 2 until the mean brightness error is satisfied the defined threshold. Then each divided group or sub-histogram will be independently equalized based on the proportional input mean. To provide the overall minimum mean brightness error, each group will be controlled by adding some certain pixels from the adjacent grey level of the next group for giving its mean near by the corresponding the divided mean. However, it still exists some little error which will be put into the next adjacent group. By successive dividing the original histogram, we found that the absolute mean brightness error is gradually decreased when the number of group is increased. Therefore, the error threshold is assigned in order to automatically dividing the original histogram for obtaining the desired absolute mean brightness error (AMBE). This process will be applied to the color image by treating each color independently.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.701-706
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• 2002

A set of color features has been efficiently used to measure the similarity of given images. However, the size of the color features is too large to implement an indexing scheme effectively. In this paper a new method is proposed to retrieve similar images using an interpolated color histogram. The idea is similar to the already reported methods that use the distributions of color histograms. The new method is different in that simplified color histograms decide the similarity between a query image and target images. In order to represent the distribution of the color histograms, the best order of interpolated polynomial has been simulated. After a histogram distribution is represented in a polynomial form, only a few number of polynomial coefficients are indexed and stored in a database as a color descriptor. The new method has been applied to real images and achieved satisfactory results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.104-115
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• 2001

A new content-based color image retrieval method integrating the features of the color adjacency and the gradient is proposed in this paper. As the most used feature of color image, color histogram has its own advantages that it is invariant to the changes in viewpoint and the rotation of the image etc., and the computation of the feature is simple and fast. However, it is difficult to distinguish those different images having similar color distributions using histogram-based image retrieval, because the color histogram is generated on uniformly quantized colors and the histogram itself contains no spatial information. And another shortcoming of the histogram-based image retrieval is the storage of the features is usually very large. In order to prevent the above drawbacks, the gradient that is the largest color difference of neighboring pixels is calculated in the proposed method instead of the uniform quantization which is commonly used at most histogram-based methods. And the color adjacency information which indicates major color composition feature of an image is extracted and represented as a binary form to reduce the amount of feature storage. The two features are integrated to allow the retrieval more robust to the changes of various external conditions.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.480-483
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• 2005

This study has proposed a method of content-based image retrieval in order to overcome disadvantages of color histogram. The existing histogram method has a weak point that reduces accuracy because of quantization error, and more. In order to solve this, we convert color information to HSV and quantize Hue factor being net color information and calculate histogram and then use this for retrieval feature that is robust in brightness, movement, and rotation. As a result of experimenting, the method proposed has showed better precision than the existing method.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.329-341
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• 2014

Kernel-based mean-shift object tracking has gained more interests nowadays, with the aid of its feasibility of reliable real-time implementation of object tracking. This algorithm calculates the best mean-shift vector based on the color histogram similarity between target model and target candidate models, where the color histograms are usually produced after uniform color-space quantization for the implementation of real-time tracker. However, when the image of target model has a reduced contrast, such uniform quantization produces the histogram model having large values only for a few histogram bins, resulting in a reduced accuracy of similarity comparison. To solve this problem, a non-uniform quantization algorithm has been proposed, but it is hard to apply to real-time tracking applications due to its high complexity. Therefore, this paper proposes a fast non-uniform color-space quantization method using the histogram equalization, providing an adjusted histogram distribution such that the bins of target model histogram have as many meaningful values as possible. Using the proposed method, the number of bins involved in similarity comparison has been increased, resulting in an enhanced accuracy of the proposed mean-shift tracker. Simulations with various test videos demonstrate the proposed algorithm provides similar or better tracking results to the previous non-uniform quantization scheme with significantly reduced computation complexity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.10
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• pp.2427-2432
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• 2014

Color-$X^2$ is used as a method for scene change detection. It extracts a violent scene in an elevator and then could be used for real-time surveillance of criminal acts. The scene could be also used to secure after-discovered evidences and to prove analysis processes. Video Forensic is defined as a research on various methods to efficiently analyze evidences upon crime-related visual images in the field of digital forensic. The method to use differences of color-histogram detects the difference values of histogram for RGB color from two frames respectively. Our paper uses Color-$X^2$ histogram that is composed of merits of color histogram and ones of $X^2$ histogram, in order to efficiently extract violent scenes in elevator. Also, we use a threshold so as to find out key frame, by use of existing Color-$X^2$ histogram. To increase the probability that discerns whether a real violent scene or not, we take advantage of statistical judgments with 20 sample visual images.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.415-420
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• 2013

In recent, many researches have been studying sensitivity and psychology of human on color. Among them, a picture of children can be a tool to represent their emotion. Information of colors and direction on a child's picture often represent his internal psychological states unconsciously. In this paper, we propose the method that extract the color and direction information in order to analyze the psychology in the picture of children. Histogram clustering is used for color information detection. Direction information extract from inner edge value. In the result of experiments, we shows that our method is similar to the pattern classification of the general method.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.49-54
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• 2014

This paper proposes a new color segmentation method of vehicle license plates in the RGB color space. Firstly, the proposed method shifts the histogram of an input image rightwards and then stretches the image of the histogram slide. Secondly, the method separates each of the three RGB color components and performs the adaptive threshold processing with the three components, respectively. Finally, it combines the three components under the condition of making up a segment color and removes noises with the morphological processing. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real vehicle images. The results show that the proposed algorithm is successful for most vehicle images. However, the method fails in some vehicles when the body and the license plate have the same color.

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.44-50
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• 2006

This study has proposed a method of content-based image retrieval using object region in order to overcome disadvantages of existing color histogram methods. The existing color histogram methods have a weak point of reducing accuracy, because these have both a quantization error and an absence of spatial information. In order to overcome this problem, we convert a color information to a HSV space, quantize hue factor being pure color information, and calculate histogram. And then we use hue for retrieval feature that is robust in brightness, movement, and rotation. To solve the problem of the absence of spatial information, we select object region in terms of color feature and region correlation. And we use both the edge and the DC in the selected region for retrieving. As a result of experiment with 1,000 natural color images, the proposed method shows better precision and recall than the existing methods.