• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.248-253
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• 2008

In this paper, a novel vehicle detection algorithm is proposed that utilizes the color histogram of the image. The color histogram is used to search the image for regions with shadow, block symmetry, and block non-homogeneity, thereby detecting the vehicle region. First, an integral histogram of the input image is computed to decrease the amount of required computation time for the block color histograms. Then, shadow detection is performed and the block symmetry and block non-homogeneity are checked in a cascade manner to detect the vehicle in the image. Finally, the proposed scheme is applied to both still images taken in a parking lot and an on-road video sequence to demonstrate its effectiveness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.603-610
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• 2008

In this paper, we propose an efficient noise reduction algorithm for digital hologram during acquisition and transmission. The proposed algorithm segment a digital hologram with object region and background region after DCT. Then, we adopt a histogram transition method for object region and zero-value change method for background region. The experimental results show that our algorithm has beuer performance than a natural image denoising algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.666-671
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• 2008

In this paper, we propose a new method for tracking objects continously and successively based on fusion of region information, color information and motion template when multiple objects are occluded and splitted. For each frame, color template is updated and compared with the present object. The predicted region, dynamic template and color histogram are used to classify the objects. The vertical histogram of the silhouettes is analyzed to determine whether or not the foreground region contains multiple objects. The proposed method can recognize more correctly the objects to be tracked.

• Proceedings of the KAIS Fall Conference
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• 2006.11a
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• pp.220-224
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• 2006

The text to be included in the natural images has many important information in the natural image. Therefore, if we can extract the text in natural images, It can be applied to many important applications. In this paper, we propose a text region extraction method using pattern histogram of character-edge map. We extract the edges with the Canny edge detector and creates 16 kind of edge map from an extracted edges. And then we make a character-edge map of 8 kinds that have a character feature with a combination of an edge map. We extract text region using 8 kinds of character-edge map and 16 kind of edge map. Verification of text candidate region uses analysis of a character-edge map pattern histogram and structural feature of text region. The method to propose experimented with various kind of the natural images. The proposed approach extracted text region from a natural images to have been composed of a complex background, various letters, various text colors effectively.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.46-51
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• 2002

In this paper, I proposed a eyebrow detection algorithm in human face, that is important element in facial recognition. The proposed algorithm consists of four processes: face region detection using color region segmentation. eye detection by template matching, eyebrow candidate region detection in detected eye region, and eyebrow detection by thresholding using the modified histogram that gets luminance value in the candidate region. The test results show that the proposed algorithm can detect eyebrow region very effectively in facial image.

• Journal of Digital Contents Society
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• v.10 no.4
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• pp.597-604
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• 2009

For the improvement of license plate recognition system, correct extraction of a license plate region as well as character recognition is important. In this paper, with the analysis and classification of the error patterns in the process of plate region extraction, we tried to improve the extraction of the region using HoG(histogram of gradient) features and Adaboost. The results show that the HoG feature is robust to the noise and various types of the plates, and also is very effective to extract the region failed before.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1207-1214
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• 2009

In this study, we propose a novel color-image segmentation algorithm to discern the teeth region utilizing RG intensity and its relevant RGB histogram features with resolving the variations of its maximum intensity in terms of peaks and valleys. Tooth candidates in a CCD image are first extracted by applying RGB color multi-threshold levels and consequently the successive morphological image operations and a Sobel-mask edge processing are performed to resolve the teeth region and its contour.

• Journal of Korea Multimedia Society
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• v.18 no.7
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• pp.806-817
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• 2015

The contrast limited adaptive histogram equalization(CLAHE) is an advanced method for the histogram equalization which is a common contrast enhancement technique. The CLAHE divides the image into sections, and applies the contrast limited histogram equalization for each section. X-ray images can be classified into three areas: skin, bone, and air area. In clinical application, the interest area is limited to the skin or bone area depending on the diagnosis region. The CLAHE could deteriorate X-ray image quality because the CLAHE enhances the area which doesn't need to be enhanced. In this paper, we propose a new method which automatically determines the clip limit of CLAHE's parameter to improve X-ray image quality using fuzzy logic. We introduce fuzzy logic which is possible to determine clip limit proportional to the interest of users. Experimental results show that the proposed method improve images according to the user's preference by focusing on the subject.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.330-335
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• 2015

Approximately 23% of traffic accidents appear to be caused by drowsiness while driving. This fact shows that drowsy driving is a big factor in many traffic accidents. Therefore, the development of a drowsiness checking system is necessary to prevent drowsy driving. In this paper, we analyse the changes of the histogram of eye region images which are acquired using a CCD camera. We develop a drowsiness checking system using this histogram change information. The experimental results show that our proposed method enhances the accuracy of checking drowsiness by nearly 98%, and can be used to prevent vehicle accidents due to the drowsiness of a driver.