• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.152-165
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• 1998

The contour coding usually occupies the biggest part in the encoded bitstream, which causes the bottleneck problem of a region-based coding scheme. In this paper, new adaptive contour coding technique is proposed for the segmentation-based image coding. By adaptive contour coding considering contrast of neighbor regions in the proposed method, the overall bitrate can be significantly reduced without loss of the subjective image quality. After segmentation using watershed algorithm to the image, the contour segments are classified according to the contrast of the adjacent regions. Then, the contour segments between classified low contrast regions are highly compressed using morphological low pass filtering. The needed bits for encoding the contour information is reduced without loss of subjective image quality in the experiment.

• Journal of KIISE
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• v.42 no.10
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• pp.1239-1246
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• 2015

Cell counting is extensively used to analyze cell growth in biomedical research, and as a result automated cell counting methods have been developed to provide a more convenient and means to analyze cell growth. However, there are still many challenges to improving the accuracy of the cell counting for cells that proliferate abnormally, divide rapidly, and cluster easily, such as cancer cells. In this paper, we present an automated cell counting method for HeLa cells, which are used as reference for cancer research. We recognize and classify the morphological conditions of the cells by using a cell segmentation algorithm based on cell membrane extraction, and we then apply a cell back-tracking algorithm to improve the cell counting accuracy in cell clusters that have indistinct cell boundary lines. The experimental results indicate that our proposed segmentation method can identify each of the cells more accurately when compared to existing methods and, consequently, can improve the cell counting accuracy.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.265-270
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• 2011

In this paper, we propose a method for intensity correction using binarization-based region segmentation in 3D stereoscopic images. In the proposed method, 3D stereoscopic right image is segmented using binarizarion. Small regions in the segmented image are eliminated. For each region in right image, a corresponding region in left image is decided through region matching using correlation coefficient. When region-based matching, in order to prevent overlap between regions, we remove a portion of the area closed to the region boundary using morphological filter. The intensity correction in left and right image can be performed through histogram specification between the corresponding regions. Simulation results show the proposed method has the smallest matching error than the conventional method when we generate the right image from the left image using block based motion compensation.

• Journal of Broadcast Engineering
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• v.18 no.5
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• pp.702-712
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• 2013

In this paper, we proposed an algorithm that extracts the airway and lung without loss of information in spite of the pulmonary vessel and nodules of the chest wall in the chest CT images. We use a mask image in order to improve the performance and to save processing time of airway and lung segmentation. In the second step, by converting left and right lungs to binary image using the morphological information, we have removed the solitary pulmonary nodule to identify the value of the threshold lung and the chest wall. The last step is to connect the outer shell of the lung with cubic Spline interpolation by adding the perfect pixel and computing the distance of the removed part. Experimental results using Matlab verified that the proposed method could overcome the drawbacks of the conventional methods.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.542-551
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• 2000

In this paper, a novel technique is presented for automatic brain region segmentation in single channel MR image data sets for 3D visualization and analysis. The method detects brain contours in 2D and 3D processing of four steps. The first and the second make a head mask and an initial brain mask by automatic thresholding using a curve fitting technique. The stage 3 reconstructs 3D volume of the initial brain mask by cubic interpolation and generates an intermediate brain mask using morphological operation and labeling of connected components. In the final step, the brain mask is refined by automatic thresholding using curve fitting. This algorithm is useful for fully automatic brain region segmentation of T1-weighted, T2-weighted, PD-weighted, SPGR MRI data sets without considering slice direction and covering a whole volume of a brain. In the experiments, the algorithm was applied to 20 sets of MR images and showed over 0.97 in comparison with manual drawing in similarity index.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.337-344
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• 1995

Because of the high energy of the treatment beam, contrast of portal films is very poor. Many image processing techniques have been applied to the portal images but a significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it may be remedied by separating the treatment field from the background prior to enhancement and uslng only the pixels within the field boundary in the enhancement procedure. A new edge extraction algorithm for accurate extraction of the radiation field boundary from portal Images has been developed for contrast enhancement of portal images. In this paper, portal image segmentation algorithm based on Sobel filtration, labelling processes and morphological thinning has been presented. This algorithm could automatically search the optimal threshold value which is sensitive to the variation of the type and quality of portal images.

• Journal of Korea Multimedia Society
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• v.2 no.4
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• pp.390-399
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• 1999

Extracting the character region(container identifier) in the image of a shipping container is one of the key factors in a system for identifying a shipping container automatically To improve the performance of the automatic recognition system for identifying a shipping container, thus a method partitioning the character region more correctly and efficiently is needed. In this paper, an efficient method is proposed to extract only the character region in the image of a shipping container. The proposed method removes noises that are not possibly related to the character using morphological operation, then the image is binarized using the threshold value that is determined from the image obtained previous step. Finally individual character area is extracted from the binary image. Also experiments are conducted to verify the efficiency of the proposed method. The results show that the proposed method partitions the character region correctly from container images.

• Journal of Species Research
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• v.6 no.spc
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• pp.185-214
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• 2017

The genus Phyllopodopsyllus T. Scott, 1906 is nearly cosmopolitan and contains around 60 valid species, but has not been previously recorded in Korea. One of the reasons is probably the paucity of research in marginal habitats, such as marine interstitial. I describe two new species here. Numerous specimens of both sexes of P. kitazimai sp. nov. were collected from a beach near Yeongdeok, while only two females of P. busanensis sp. nov. were collected from a beach near Busan. The new species differ in numerous macro-morphological characters, such as the segmentation and armature of the antennula, armature of the mandibula, maxillula, maxilliped, and the first three swimming legs, as well as the shape of the caudal rami and the female genital field. However, they show very little difference in the number and position of cuticular organs (pores and sensilla) on all somites, which might prove these rarely used micro-characters to be useful in the reconstruction of phylogenetic relationships in this group of harpacticoids. Both species have their closest relatives in Japan. Phyllopodopsyllus kitazimai is morphologically most similar to P. punctatus Kitazima, 1981, but can be distinguished by much longer third exopodal segments of the third and fourth swimming legs. Phyllopodopsyllus busanensis shares the largest number of morphological similarities with P. setouchiensis Kitazima, 1981, but can be distinguished by shorter caudal rami. A key to species is also provided.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.92-98
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• 2022

This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.2
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• pp.50-59
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• 2000

In this paper, a new preprocessing method is proposed to speedup the watershed-based image segmentation In the proposed method, the gradient correction values of ramp edges are calculated from the positions and width of the ramp edges using Laplacian operator, and then, unlike the conventional method in which the monoscale or multi scale gradient image is directly used as a reference iImage, the reference image is obtained by adding the threshold value to each position of the ramp edges in the monoscale gradient image And the marker image is reconstructed on the reference image by erosion By preprocessing the image for the watershed transformation in such a manner, we can reduce the oversegmentations far more than those of applying the conventional morphological filter to the simple monoscale or multiscale gradient-based reference image Thus, we can reduce the total image segmentation time by reducing the time of postprocessing of region merging, which consumes most of the processing time In the watershed-based image segmentation, Experimental results indicate that the proposed method can speedup the total image segmentation about twice than those of the conventional methods, without the loss of ramp edges and principal edges around the dense-edge region.