• ETRI Journal
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• v.17 no.1
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• pp.23-36
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• 1995

We present a performance evaluation model of cell reassembly mechanism in an ATM switching system. An ATM switching system may be designed so that communications between processors of its control part can be performed via its switching network rather than a separate inter-processor communications network. In such a system, there should be interface to convert inter-processor communication traffic from message format to cell format and vice versa, that is, mechanisms to perform the segmentation and reassembly sublayer. In this paper, we employ a continuous-time Markov chain for the performance evaluation model of cell reassembly mechanism with individual buffering, judicially defining the states of the mechanism. Performance measures such as message loss probability and average reassembly delay are obtained in closed forms. Some numerical illustrations are given for the performance analysis and dimensioning of the cell reassembly mechanism.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.108-115
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• 2001

In this paper we are attempted to quantitative classification of the three object color regions on a RGB image using of an improved ML(Maximum Likelihood) classification method. A RGB color image consists of three bands i.e., red, green and blue. Therefore it has a 3 dimensional structure in view of the spectral and spatial elements. The 3D structural yokels were projected in RGB cube wherefrom the ML method applied. Between the conventionally and easily usable Box classification and the statistical ML classification based on Bayesian decision theory, we compared and reviewed. Using the ML method we obtained a good segmentation result to classify positive cell nucleus, negative cell Nucleus and background un a immuno-histological breast carcinoma image. Hopefully it is available to diagnosis and prognosis for cancer patients.

• Molecules and Cells
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• v.27 no.5
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• pp.497-502
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• 2009

In mouse embryos, somite formation occurs every two hours, and this periodic event is regulated by a biological clock called the segmentation clock, which involves cyclic expression of the basic helix-loop-helix gene Hes7. Hes7 expression oscillates by negative feedback and is cooperatively regulated by Fgf and Notch signaling. Both loss of expression and sustained expression of Hes7 result in severe somite fusion, suggesting that Hes7 oscillation is required for proper somite segmentation. Expression of a related gene, Hes1, also oscillates by negative feedback with a period of about two hours in many cell types such as neural progenitor cells. Hes1 is required for maintenance of neural progenitor cells, but persistent Hes1 expression inhibits proliferation and differentiation of these cells, suggesting that Hes1 oscillation is required for their proper activities. Hes1 oscillation regulates cyclic expression of the proneural gene Neurogenin2 (Ngn2) and the Notch ligand Delta1, which in turn lead to maintenance of neural progenitor cells by mutual activation of Notch signaling. Taken together, these results suggest that oscillatory expression with short periods (ultradian oscillation) plays an important role in many biological events.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.103-113
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• 2019

Motivation: Polymerized actin-based cytoskeletal structures are crucial in shape, dynamics, and resilience of a cell. For example, dynamical actin-containing ruffles are located at leading edges of cells and have a significant impact on cell motility. Other filamentous actin (F-actin) bundles, called stress fibers, are essential in cell attachment and detachment. For this reason, their mechanistic understanding provides crucial information to solve practical problems related to cell interactions with materials in tissue engineering. Detecting and counting actin-based structures in a cellular ensemble is a fundamental first step. In this research, we suggest a new method to characterize F-actin wrapping fibers from confocal fluorescence image stacks. As fluorescently labeled F-actin often envelope the fibers, we first propose to segment these fibers by diminishing an energy based on maximum flow and minimum cut algorithm. The actual actin is detected through the use of bilateral filtering followed by a thresholding step. Later, concave actin bundles are detected through a graph-based procedure that actually determines if the considered actin filament is enclosing the fiber.

• Journal of Biomedical Engineering Research
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• v.44 no.3
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• pp.176-181
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• 2023

During cancer treatment, the patient's response to drugs appears differently at the cellular level. In this paper, an image-based cell phenotypic feature quantification and key feature selection method are presented to predict the response of patient-derived cancer cells to a specific drug. In order to analyze the viability characteristics of cancer cells, high-definition microscope images in which cell nuclei are fluorescently stained are used, and individual-level cell analysis is performed. To this end, first, image stitching is performed for analysis of the same environment in units of the well plates, and uneven brightness due to the effects of illumination is adjusted based on the histogram. In order to automatically segment only the cell nucleus region, which is the region of interest, from the improved image, a superpixel-based segmentation technique is applied using the fluorescence expression level and morphological information. After extracting 242 types of features from the image through the segmented cell region information, only the features related to cell viability are selected through the ReliefF algorithm. The proposed method can be applied to cell image-based phenotypic screening to determine a patient's response to a drug.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.708-713
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• 2004

A method of individual vehicle detection using gray scale image acquired from a high position is proposed for guidance of incoming vehicles to vacant cells in a parking lot and other similar purposes. With the proposed method, each image region corresponding to a cell is fragmented according to density(gray level), and the distribution of segment area is analyzed to decide if a vehicle is present. The proposed method was tested on an actual outdoor parking lot during 2 days with different weather conditions from sunrise through sunset.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.18-26
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• 2019

In this paper we propose how to detect circular objects in the gray scale image and segment them using the discrete Morse theory, which makes it possible to analyze the topology of a digital image, when it is transformed into the data structure of some combinatorial complex. It is possible to get meaningful information about how many connected components and topologically circular shapes are in the image by computing the persistent homology of the filtration using the Morse complex. We obtain a Morse complex by modeling an image as a cubical cellular complex. Each cell in the Morse complex is the critical point at which the topological structure changes in the filtration consisting of the level sets of the image. In this paper, we implement the proposed algorithm of segmenting the circularly shaped objects with a long persistence of homology as well as computing persistent homology along the filtration of the input image and displaying in the form of a persistence diagram.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.2
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• pp.139-151
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• 1997

An ATM switching system may be designed so that communications between processors of its control part can be performed via its switching network rather than a separate inter-processor communications (IPC) network. In such a system, there should be interfaces to convent IPC traffic from message format to cell format and vice versa, that is, mechanisms to perform the SAR (Segmentation And Reassembly) sublayer functions. In this paper, we concern the cell reassembly mechanism among them, mainly focussed on buffer management schemes. We consider a few alternatives to implement cell reassembly function block, namely, separated buffering, reserved buffering and shared buffering in this paper. In case of separated and reserved buffering, we employ a continuous time Markov chain for the performance evaluation of cell reassembly mechanism, judicially defining the states of the mechanism. Performance measures such as measage loss probability, mean number of message queued in buffer and average reassembly delay are obtianed in closed forms. In case of shared buffering, we compare the alternatives for implementing cell reassembly function block using simulation because it is almost impossible to analyze the mechanism of shared buffering by analytical modeling. Some illustrations are given for the performance analysis of the alternatives to implement cell reassembly function block.

• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.99-111
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• 2009

The result of Image segmentation, an indispensable process in image processing, significantly affects the analysis of an image. Despite the significance of image segmentation, it produces some problems when the variation of pixel values is large, or the boundary between background and an object is not clear. Also, these problems occur frequently when many objects in an image are placed very close by. In this paper, when the shape of objects in an image is circular, we proposed an algorithm which segment an each object in an image using the geometric characteristic of circular shape. The proposed algorithm is composed of 4 steps. First is the boundary edge extraction of whole object. Second step is to find the candidate points for further segmentation using the boundary edge in the first step. Calculating the representative circles using the candidate points is the third step. Final step is to draw the line connecting the overlapped points produced by the several erosions and dilations of the representative circles. To verify the efficiency of the proposed algorithm, the algorithm is compared with the three well-known cell segmentation algorithms. Comparison is conducted by the number of segmented region and the correctness of the inner segment line. As the result, the proposed algorithm is better than the well-known algorithms in both the number of segmented region and the correctness of the inner segment line by 16.7% and 21.8%, respectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.28-36
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• 2022

As port structures are exposed to various extreme external loads such as wind (typhoons), sea waves, or collision with ships; it is important to evaluate the structural safety periodically. To monitor the port structure, especially the rubber fender, a fender segmentation system using a vision sensor and deep learning method has been proposed in this study. For fender segmentation, a new deep learning network that improves the encoder-decoder framework with the receptive field block convolution module inspired by the eccentric function of the human visual system into the DenseNet format has been proposed. In order to train the network, various fender images such as BP, V, cell, cylindrical, and tire-types have been collected, and the images are augmented by applying four augmentation methods such as elastic distortion, horizontal flip, color jitter, and affine transforms. The proposed algorithm has been trained and verified with the collected various types of fender images, and the performance results showed that the system precisely segmented in real time with high IoU rate (84%) and F1 score (90%) in comparison with the conventional segmentation model, VGG16 with U-net. The trained network has been applied to the real images taken at one port in Republic of Korea, and found that the fenders are segmented with high accuracy even with a small dataset.