• Journal of Advanced Navigation Technology
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• v.15 no.4
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• pp.672-679
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• 2011

In this paper, detection algorithm of face region based on skin color of in the TV images is proposed. In the first, reference image is set to the sampled skin color, and then the extracted of face region is candidated using the Euclidean distance between the pixels of TV image. The eye image is detected by using the mean value and standard deviation of the component forming color difference between Y and C through the conversion of RGB color into CMY color model. Detecting the lips image is calculated by utilizing Q component through the conversion of RGB color model into YIQ color space. The detection of the face region is extracted using basis of knowledge by doing logical calculation of the eye image and lips image. To testify the proposed method, some experiments are performed using front color image down loaded from TV color image. Experimental results showed that face region can be detected in both case of the irrespective location & size of the human face.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.894-897
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• 2000

In this paper, we present a content-based image retrieval method that is less sensitive to some rotations and translations of an image by using the fuzzy region segmentation. The algorithm retrieves similar images from a database using the two features of color and color spatial information. To index images, we use the average coordinates of color distribution to obtain the spatial information of each segmented region. Furthermore, we also propose the alternative to the ripple phenomenon, which is occurred in the conventional fuzzy region segmentation algorithm.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.7-13
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• 2018

The methods for detecting copy move frogery (CMF) are divided into two categories, block-based methods and keypoint-based methods. Block-based methods have a high computational cost because a large number of blocks should be examined for CMF detection. In addition, the forgery detection may fail if a tampered region undergoes geometric transformation. On the contrary, keypoint-based methods can overcome the disadvantages of the block-based approach, but it can not detect a tampered region if the CMF forgery occurs in the low entropy region of the image. Therefore, in this paper, we propose a method to detect CMF forgery in all areas of image by combining keypoint-based and block-based methods. The proposed method first performs keypoint-based CMF detection on the entire image. Then, the areas for which the forgery check is not performed are selected and the block-based CMF detection is performed for them. Therefore, the proposed CMF detection method makes it possible to detect CMF forgery occurring in all areas of the image. Experimental results show that the proposed method achieves better forgery detection performance than conventional methods.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.5
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• pp.314-318
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• 2010

This paper proposes an image retrieval method based on the Multiple Region-of-Interest. In the proposed method, the image is segmented into blocks, among which the blocks overlapped with multiple ROIs are selected. The similarity of images is measured using the MPEG-7 dominant color descriptor(DCD) and considering the relative location of the overlapped blocks. The experimental results showed that the proposed method improves the retrieval performance than the previous methods using the global DCD or comparing the blocks at the same position. In addition, the method that considers the relative position of blocks overlapped with the multiple ROIs also showed a better performance than the existing methods.

• Journal of the Korean Wood Science and Technology
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• v.50 no.6
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• pp.490-498
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• 2022

The current study aimed to verify the image segmentation ability of rays in tangential thin sections of conifers using artificial intelligence technology. The applied model was Mask region-based convolutional neural network (Mask R-CNN) and softwoods (viz. Picea jezoensis, Larix gmelinii, Abies nephrolepis, Abies koreana, Ginkgo biloba, Taxus cuspidata, Cryptomeria japonica, Cedrus deodara, Pinus koraiensis) were selected for the study. To take digital pictures, thin sections of thickness 10-15 ㎛ were cut using a microtome, and then stained using a 1:1 mixture of 0.5% astra blue and 1% safranin. In the digital images, rays were selected as detection objects, and Computer Vision Annotation Tool was used to annotate the rays in the training images taken from the tangential sections of the woods. The performance of the Mask R-CNN applied to select rays was as high as 0.837 mean average precision and saving the time more than half of that required for Ground Truth. During the image analysis process, however, division of the rays into two or more rays occurred. This caused some errors in the measurement of the ray height. To improve the image processing algorithms, further work on combining the fragments of a ray into one ray segment, and increasing the precision of the boundary between rays and the neighboring tissues is required.

• Journal of Korea Multimedia Society
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• v.18 no.10
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• pp.1172-1179
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• 2015

A wireless license plate region extracting module is proposed for LPR system controlling multiple gates. This module is cheaply implemented using Raspberry Pi which is open source and high performance. First, as the upper 1/3 of the captured image is discarded as it has no useful information on license plate. Using the OpenCV libraries the edge image is got by Canny algorithm after applying Gaussian filtering to gray image, and the labeling is conducted for 4 consecutive numbers in license plate. These numbers are located using various decision equations, and expanding the numbers region the final license plate region can be extracted. The result image is transferred to Server using wifi direct. Using the proposed module it becomes easy to set up and maintain the LPR system. The experimental results showed that the successful extracting rate was 98.4% using 500 car images with 640 × 480 resolution.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.801-802
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• 2008

This paper presents a new dynamic range compression method using region-adaptive gamma correction. Gamma corrections with different gamma coefficients are first applied to the observed image to generate several candidate images. Then, the proposed method produces the result image by adequately combining them according to the weight function based on local variances. Experimental results demonstrate that the proposed method significantly enhances image quality by bringing out the details not only in dark region but also in bright region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.597-605
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• 1999

In this paper, we propose a cardioangiography sequence image coding scheme which use a subtraction between initial image and current frame inserted contrast dye. Stable regions are obtained by the multithreshold and meaningful region is extracted by the images with stable region. The image with meaningful region is classified into contour and texture information. Contour information is coded by contour coding. And texture information is approximated by two-dimensional polynomial function and each coefficients is coded. Experimental results confirm that the sequence of cardioangiography are well reconstructed at the low bit rate (0.02∼0.04 bpp) and high compression ratio.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.187-193
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• 2021

In this paper, we propose an image watermarking technique that effectively hides confidential data in the LSB of image pixels by utilizing the characteristics of the image. In the proposed technique, the image is precisely divided into boundary surface and normal region other than the boundary surface and performs different processing. The boundary surface existing in the image is created by meeting different regions and contains important information of the image. One bit of confidential data is concealed in the LSB of the pixel at the boundary surface to preserve the characteristics of the boundary surface. In normal region other than the boundary surface, the pixel values are similar, and the change with the adjacent pixel values is smooth. Based on this property, even if the 2 bits of confidential data are hidden in the lower 2 bits of the pixel in the normal region, the difference cannot be visually distinguished. When confidential data is concealed in an image as described above, the amount of confidential data concealed in an image can be increased while maintaining excellent image quality. Concealing confidential data by applying the proposed method increases the amount of confidential data concealed by up to 84.6% compared to the existing method. The proposed technique can be effectively used for commercial image watermarking that hides copyright information.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.99-102
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• 2009

In this paper a hierarchical stereo matching algorithm based on feature extraction is proposed. The boundary (edge) as feature point in an image is first obtained by segmenting an image into red, green, blue and white regions. With the obtained boundary information, disparities are extracted by matching window on the image boundary, and the initial disparity map is generated when assigned the same disparity to neighbor pixels. The final disparity map is created with the initial disparity. The regions with the same initial disparity are classified into the regions with the same color and we search the disparity again in each region with the same color by changing block size and search range. The experiment results are evaluated on the Middlebury data set and it show that the proposed algorithm performed better than a phase based algorithm in the sense that only about 14% of the disparities for the entire image are inaccurate in the final disparity map. Furthermore, it was verified that the boundary of each region with the same disparity was clearly distinguished.