• Journal of Sensor Science and Technology
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• v.13 no.1
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• pp.56-65
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• 2004

In this paper, we proposed the detection algorithm of microcalcification based on region growing method with contrast and edge sharpness in digital X-ray mammographic images. We extracted the local maximum pixel and watershed regions by using watershed algorithm. Then, we used the mean slope between local maximum and neighborhood pixels to extract microcalcification candidate pixels among local maximum pixels. During increasing threshold value to grow microcalcification region, at the maximum threshold value of the contrast and edge sharpness, the microcalcification area is decided. The regions of which area of grown candidate microcalfication region is larger than that of watershed region are excluded from microcalcifications. We showed the diagnosis algorithm can be used to aid diagnostic-radiologist in the early detection breast cancer.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.531-532
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• 2017

OneM2M's domain is divided into Device, Network, and Application domain, and data generated from various devices is collected through IoT/M2M gateway, it is delivered to appropriate IoT/M2M Infrastructure through Core/Access Network. However, access to the Core/Access Network is also required if the device transmit data to an Infrastructure located within the same area. In this paper, it propose data transmission based on region gateway that judge and transmit local information of data by adding a concept of region network domain to oneM2M domain, prevent access to unnecessary Core/Access Network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.198-201
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• 2009

In this paper, an eye tracking method is presented by using on iterated spatial moment adapting weighted gray level that can accurately detect and track user's eyes under the complicated background. The region of face is detected by using Haar-like feature before extracting region of eyes to minimize an region of interest from the input picture of CCD camera. And the region of eyes is detected by using eigeneye based on the eigenface of Principal component analysis. And then feature points of eyes are detected from darkest part in the region of eyes. The tracking of eyes is achieved correctly by using iterated spatial moment adapting weighted gray level.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.283-289
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• 2006

The present image segmentation is what user want to segment image and has been studied for technology in composition of segment object with other images. In this paper, we propose a method of novel semi-automatic image segmentation using gradual region merging and genetic algorithm. Proposed algorithm is edge detection of object using genetic algorithm after selecting object which user want. We segment region of object which user want to based on detection edge using watershed algorithm. We separated background and object in indefinite region using gradual region merge from Segment object. And, we have applicable value which user want by making interface based on GUI for efficient perform of algorithm development. In the experiments, we analyzed various images for proving superiority of the proposed method.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.1-8
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• 2021

Prostate cancer is one of the most diagnosed malignancies found across the world today. American cancer society in recent research predicted that over 174,600 new prostate cancer cases found and nearly 31,620 death cases recorded. Researchers are developing modest and accurate methodologies to detect and diagnose prostate cancer. Recent work has been done in radiology to detect prostate tumors using ultrasound imaging and resonance imaging techniques. Transrectal ultrasound and Magnetic resonance images of the prostate gland help in the detection of cancer in the prostate gland. The proposed paper is based on comparison and analysis between two novel image segmentation approaches. Seed region growing and cluster based image segmentation is used to extract the region from trans-rectal ultrasound prostate and MR prostate images. The region of extraction represents the abnormality area that presents in men's prostate gland. Detection of such abnormalities in the prostate gland helps in the identification and treatment of prostate cancer

• Structural Engineering and Mechanics
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• v.88 no.1
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• pp.13-23
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• 2023

Seismic risk assessment studies are one of the most crucial instruments for mitigating casualties and economic losses. This work utilizes fragility curves to evaluate the seismic risk of single-story precast buildings, which are generally favored in Marmara's organized industrial zones. First, the precast building stock in the region has been categorized into nine sub-classes. Then, seven locations in the Marmara region with a high concentration of industrial activities are considered. Probabilistic seismic hazard assessments were conducted for both the soil-dependent and soil-independent scenarios. Subsequently, damage analysis was performed based on the structural capacity and mean fragility curves. Considering four different consequence models, 630 sub-class-specific loss curves for buildings were obtained. In the current study, it has been determined that the consequence model has a significant impact on the loss curves, hence, average loss curves were computed for each case investigated. In light of the acquired results, it was found that the loss ratio values obtained at different locations within the same region show significant variation. In addition, it was observed that the structural damage states change from serviceable to repairable or repairable to unrepairable. Within the scope of the study, 126 average loss functions were presented that could be easily used by non-experts in earthquake engineering, regardless of structural analysis. These functions, which offer loss ratios for varying hazard levels, are valuable outputs that allow preliminary risk assessment in the region and yield sensible outcomes for insurance activities.

• Korean journal of food and cookery science
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• v.21 no.3 s.87
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• pp.271-282
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• 2005

In this study a survey was conducted to compare the foods prepared for the Korean ancestral service on Memorial Day, Thanksgiving Day and New Year's Day in the Yeosu and Pusan areas. Me(tap) as the main food in the rituals was highly used on New Year's Day in the Pusan region, whereas Tteokguk was highly used in the Yeosu region. As for soup ingredients in the rituals, jogae, soegogi and mu were more frequently used in the Pusan region than in the Yeosu region on Memorial Day and festive days. Jogijjim, gaorijjim, sangeojjim, myeongtaejjim, galbijjim, dakjjim, and bugeojjim were highly used in the Yeosu region but cheongeojjim and domijjim were highly used in the Pusan region. Gosari and doraji namul were highly used in both regions but most vegetables were hishly used in the fきn region except for sukju and chwi namul. Jogi gui was the most common in both regions, whereas seodae, yangtae and byeongeo-gui were highly used in the Yeosu region but dubu, jogi and mineo-gui were highly used in the Pusan region. Songpyeon injeolmi, gangjeong, and yakgwa were highly used in the Pusan region. Most fruits except apple were highly used in the Pusan region. With regard to the liquor used for the rituals, there was no difference in the use of cheongju between the two areas, whereas takju was highly used in the Pusan region but soju was highly used in the Yeosu region. The results of this study showed that the use of ritual foods varied a little according to the region and that ritual food use was based on seasonal foods, preference of ancestors, and special products of the region.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.72-75
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• 2008

Image segmentation techniques becoming increasingly important in the field of remote sensing image analysis in areas such as object oriented image classification. This paper presents a new method for image segmentation in High Resolution Remote Sensing Image based on Seeded Region Growing (SRG) and Edge Information. Firstly, multi-spectral edge detection was done using an entropy operator in pan-sharpened QuickBird imagery. Then, the initial seeds were automatically selected from the obtained edge map. After automatic selection of significant seeds, an initial segmentation was achieved by applying SRG. Finally the region merging process, using region adjacency graph (RAG), was carried out to get the final segmentation result. Experimental results demonstrated that the proposed method has good potential for application in the segmentation of high resolution satellite images.

• ETRI Journal
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• v.37 no.5
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• pp.1023-1031
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• 2015

In infrared (IR) images, near targets have a transient distribution at the boundary region, as opposed to a steady one at the inner region. Based on this fact, this paper proposes a novel IR target extraction method that uses both a weighted information entropy (WIE) and an adaptive opening filter to extract near finely shaped targets in IR images. Firstly, the boundary region of a target is detected using a local variance WIE of an original image. Next, a coarse target region is estimated via a labeling process used on the boundary region of the target. From the estimated coarse target region, a fine target shape is extracted by means of an opening filter having an adaptive structure element. The size of the structure element is decided in accordance with the width information of the target boundary and mean WIE values of windows of varying size. Our experimental results show that the proposed method obtains a better extraction performance than existing algorithms.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.39-46
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• 2019

This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.