• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.865-871
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• 2022

In this paper, we propose a method of extracting prostate region using morphological characteristics of ultra-sonic image of prostate. In the first step of the proposed method, the edge area of the prostate image is extracted. The histogram of ultra-sonic image is used to extract base objects to detect the upper edge of prostate region by altering the contrast of the image, then, the lower edges of the extracted base objects are connected by using monotone cubic spline interpolation to extract the upper edge. Step 2, Otsu's binarization is applied to the region under the extracted upper edge of the prostate ultra-sonic image to extract the lower edge of prostate. In the last step, the upper and the lower edges are connected to extract prostate region and by comparing the extracted region of prostate with the one measured manually, the result showed that the morphological characteristics of prostate in ultrasonic image can be utilized to extract the prostate region.

• Smart Media Journal
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• v.2 no.2
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• pp.8-13
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• 2013

Nowadays, the saliency region detection has become a popular research topic because of its uses for many applications like object recognition and object segmentation. Some of recent methods apply color distinctiveness based on an analysis of statistics of color image derivatives in order to boosting color saliency can produce the good saliency maps. However, if the salient regions comprise more than half the pixels of the image or the background is complex, it may cause bad results. In this paper, we introduce the method to handle these problems by using maximum symmetric surround. The results show that our method outperforms the previous algorithms. We also show the segmentation results by using Otsu's method.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.285-293
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• 2024

This study explores the use of Sentinel-1 Synthetic Aperture Radar (SAR), processed through Google Earth Engine (GEE), to monitor changes in the areas of Antarctic ice shelves. Focusing on the Campbell Glacier Tongue (CGT) and Drygalski Ice Tongue (DIT),the research utilizes GEE's cloud computing capabilities to handle and analyze large datasets. The study employs Otsu's method for image binarization to distinguish ice shelves from the ocean and mitigates detection errors by averaging monthly images and extracting main regions. Results indicate that the CGT area decreased by approximately 26% from January 2016 to January 2024, primarily due to calving events,while DIT showed a slight increase overall,with notable reduction in recent years. Validation against Sentinel-2 optical images demonstrates high accuracy,underscoring the effectiveness of SAR and GEE for continuous, long-term monitoring of Antarctic ice shelves.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.331-342
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• 1989

This paper presents a new algorithm that extracts lung region in X-Rays and enhance.j the region. Comparing to prior algorithms that enhance whole X-Ray image, this algorithm leads more effective results. For this algorithm extracts lung region first, and enhances the lung region excluding parameters of other region. For choosing optimal threshold, we compare OTSU's mothod with the proposed method. We obtain lung boundary using contour following algorithm and Rray level searching method in gray level rescaled image. We Process histogram equalization in lung region and obtain enhanced lung image. By using the proposed algorithm, we obtain lung region effectively in chest X-Ray that need in medical image diagnostic system.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10b
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• pp.162-166
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• 2003

In combined forward-backward extrusion with controlled forward speed by a counter punch, accurate parts with forward rod can be formed. As an extension of this method, reverse extrusion is proposed, in which the extruded forward rod is pushed back while the main punch is kept at the final position after the forward-backward extrusion process. The experiment is carried out using lead as a model material. With the reverse extrusion method, longer forward rods can be formed without under-filling defect than that by combined extrusion with controlling extrusion speed.

• Journal of ILASS-Korea
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• v.25 no.2
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• pp.74-80
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• 2020

The jet in crossflow is a spray method used in the various air-breathing engine. In order to understand the spray characteristics in various environments, many prior studies have been conducted. However, there is a lack of understanding of the low-temperature liquid spray characteristics below 273 K. With this in mind, we tried to enhance the knowledge of the low-temperature liquid spray characteristics by identifying the penetration height of low-temperature ethanol. The experiment was conducted under phase pressure, and 273 K of air and 293, 263, and 233 K of ethanol was used. Shadowgraphy was employed to measure the liquid penetration, and Otsu's method was used to analyze the penetration height. The heights tend to decrease as the temperature of the liquid jet decreases. A correlation for the penetration height in the experimental conditions was derived and presented.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.283-284
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• 2006

In this paper, we propose a novel segmentation and classification method using texture features for the document image. First, we extract the local entropy and then segment the document image to separate the background and the foreground using the Otsu's method. Finally, we classify the segmented regions into each component using PCA(principle component analysis) algorithm based on the texture features that are extracted from the co-occurrence matrix for the entropy image. The entropy-based segmentation is robust to not only noise and the change of light, but also skew and rotation. Texture features are not restricted from any form of the document image and have a superior discrimination for each component. In addition, PCA algorithm used for the classifier can classify the components more robustly than neural network.

• Journal of Biomedical Engineering Research
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• v.12 no.2
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• pp.89-98
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• 1991

This study is concerned on the automation for cell diagnosis which has better objectivity and speed of test than human beings. Diagnosis is on the basis of shape change of abnormal Cells. Used parameters are nucleus area, nucleus perimeter, nucleus shape, cytoplasm area, nucleus/cytoplsm ratio, which was obtained using image processing technics. A new mode method is proposed on the automatic threshold selection for superior process time compared with Otsu's. Contour of the cytoplasm of abnormal cell is obtained using me- dian filter and sorel operator. The mask to get only original shape of abnormal cells is formed uslng the contour filling algorithm. In the result the normal cells are separated from the abnormal cells and the abnormal cells can be distinguished through screwing of abnormal cell's image with reference data to judge abnormal cells. Owing to this study the number of inspections which the pathologists should examine will be decreased and the time for inspection will be shortened.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.42-50
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• 2008

We developed a visual inspection system for detecting defective products. Most existing inspection systems are designed to be dedicated to one product, which makes operator spend extra money and time to adopt other products. In this work, we propose a flexible visual inspection system that can inspect various products without any additional major job at a low-cost. The developed system contained image processing algorithm libraries and user-friendly graphic interface for adaptable image-based inspection system. We can find a proper threshold value using the proposed algorithm which uses correlation coefficient between a non-defective product and existing sample images of defective product. And We tested the performance of the proposed algorithm using Otsu's method. The proposed system is applied to a automated inspection line for cellular phone.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.363-374
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• 2010

In this paper, we propose the method for extracting Homogeneity Threshold($H_T$) and for segmenting homogeneous regions by USRG(Unseeded Region Growing) with $H_T$. The $H_T$ is a criterion to distinguish homogeneity in neighbor pixels and is computed automatically from the original image by proposed method. Theoretical background for proposed method is based on the Otsu's single level threshold method. The method is used to divide a small local part of original image int o two classes and the sum($\sigma_c$) of standard deviations for the classes to satisfy special conditions for distinguishing as different regions from each other is used to compute $H_T$. To find validity for proposed method, we compare the original image with the image that is regenerated with only the segmented homogeneous regions and show up the fact that the difference between two images is not exist visually and also present the steps to regenerate the image in order the size of segmented homogeneous regions and in order the intensity that includes pixels. Also, we show up the validity of proposed method with various results that is segmented using the homogeneity thresholds($H^*_T$) that is added a coefficient ${\alpha}$ for adjusting scope of $H_T$. We expect that the proposed method can be applied in various fields such as visualization and animation of natural image, anatomy and biology and so on.