• Title/Summary/Keyword: Otsu Method

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Segmentation Performance Analysis of the Otsu Algorithm for Spent Nuclear Fuel Cladding Image According to Morphological Operations

  • Jee A Baik;Jun Won Choi;Jung Jin Kim
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.22 no.3
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    • pp.301-311
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    • 2024
  • Hydride analysis is required to assess the mechanical integrity of spent nuclear fuel cladding. Image segmentation, which is a hydride analysis method, is a technique that can analyze the orientation and distribution of hydrides in cladding images of spent nuclear fuels. However, the segmentation results varied according to the image preprocessing. Inaccurate segmentation results can make hydride difficult to analyze. This study aims to analyze the segmentation performance of the Otsu algorithm according to the morphological operations of cladding images. Morphological operations were applied to four different cladding images, and segmentation performance was quantitatively compared using a histogram, between-class variance, and radial hydride fraction. As a result, this study found that morphological operations can induce errors in cladding images and that appropriate combinations of morphological operations can maximize segmentation performance. This study emphasizes the importance of image preprocessing methods, suggesting that they can enhance the accuracy of hydride analysis. These findings are expected to contribute to the advancements in integrity assessment of spent nuclear fuel cladding.

Development of a Method for Tracking Sandbar Formation by Weir-Gate Opening Using Multispectral Satellite Imagery in the Geumgang River, South Korea (금강에서 다분광 위성영상을 이용한 보 운영에 따른 모래톱 형성 추적 방법의 개발)

  • Cheolho Lee;Kang-Hyun Cho
    • Ecology and Resilient Infrastructure
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    • v.10 no.4
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    • pp.135-142
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    • 2023
  • A various technology of remote sensing and image analysis are applied to study landscape changes and their influencing factors in stream corridors. We developed a method to detect landscape changes over time by calculating the optical index using multispectral images taken from satellites at various time points, calculating the threshold to delineate the boundaries of water bodies, and creating binarized maps into land and water areas. This method was applied to the upstream reach of the weirs in the Geumgang River to track changes in the sandbar formed by the opening of the weir gate. First, we collected multispectral images with a resolution of 10 m × 10 m taken from the Sentinel-2 satellite at various times before and after the opening of the dam in the Geumgang River. The normalized difference water index (NDWI) was calculated using the green light and near-infrared bands from the collected images. The Otsu's threshold of NDWI calculated to delineate the boundary of the water body ranged from -0.0573 to 0.1367. The boundary of the water area determined by remote sensing matched the boundary in the actual image. A map binarized into water and land areas was created using NDWI and the Otsu's threshold. According to these results of the developed method, it was estimated that a total of 379.7 ha of new sandbar was formed by opening the three weir floodgates from 2017 to 2021 in the longitudinal range from Baekje Weir to Daecheong Dam on the Geumgang River. The landscape detection method developed in this study is evaluated as a useful method that can obtain objective results with few resources over a wide spatial and temporal range.

A Comparative Study of Reservoir Surface Area Detection Algorithm Using SAR Image (SAR 영상을 활용한 저수지 수표면적 탐지 알고리즘 비교 연구)

  • Jeong, Hagyu;Park, Jongsoo;Lee, Dalgeun;Lee, Junwoo
    • Korean Journal of Remote Sensing
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    • v.38 no.6_3
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    • pp.1777-1788
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    • 2022
  • The reservoir is a major water supply source in the domestic agricultural environment, and the monitoring of water storage of reservoirs is important for the utilization and management of agricultural water resource. Remote sensing via satellite imagery can be an effective method for regular monitoring of widely distributed objects such as reservoirs, and in this study, image classification and image segmentation algorithms are applied to Sentinel-1 Synthetic Aperture Radar (SAR) imagery for water body detection in 53 reservoirs in South Korea. Six algorithms are used: Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), Otsu, Watershed (WS), and Chan-Vese (CV), and the results of water body detection are evaluated with in-situ images taken by drones. The correlations between the in-situ water surface area and detected water surface area from each algorithm are NN 0.9941, SVM 0.9942, RF 0.9940, Otsu 0.9922, WS 0.9709, and CV 0.9736, and the larger the scale of reservoir, the higher the linear correlation was. WS showed low recall due to the undetected water bodies, and NN, SVM, and RF showed low precision due to over-detection. For water body detection through SAR imagery, we found that aquatic plants and artificial structures can be the error factors causing undetection of water body.

A shot change detection algorithm based on frame segmentation and object movement (프레임 블록화와 객체의 이동을 이용한 샷 전환 탐지 알고리즘)

  • Kim, Seung-Hyun;Hwang, Doosung
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.5
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    • pp.21-29
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    • 2015
  • This paper proposes a shot change detection algorithm by using frame segmentation and the object changes among moving blocks. In order to detect the rapid moving changes of objects between two consecutive frames, the moving blocks on the diagonal are defined, and their histograms are calculated. When a block of the current frame is compared to the moving blocks of the next frame, the block histograms are used and the threshold of a shot change detection is automatically adjusted by Otsu's threshold method. The proposed algorithm was tested for the various types of color or gray videos such as films, dramas, animations, and video tapes in National Archives of Korea. The experimental results showed that the proposed algorithm could enhance the detection rate when compared to the studied methods that use brightness, histogram, or segmentation.

IR Image Segmentation using GrabCut (GrabCut을 이용한 IR 영상 분할)

  • Lee, Hee-Yul;Lee, Eun-Young;Gu, Eun-Hye;Choi, Il;Choi, Byung-Jae;Ryu, Gang-Soo;Park, Kil-Houm
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.2
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    • pp.260-267
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    • 2011
  • This paper proposes a method for segmenting objects from the background in IR(Infrared) images based on GrabCut algorithm. The GrabCut algorithm needs the window encompassing the interesting known object. This procedure is processed by user. However, to apply it for object recognition problems in image sequences. the location of window should be determined automatically. For this, we adopted the Otsu' algorithm for segmenting the interesting but unknown objects in an image coarsely. After applying the Otsu' algorithm, the window is located automatically by blob analysis. The GrabCut algorithm needs the probability distributions of both the candidate object region and the background region surrounding closely the object for estimating the Gaussian mixture models(GMMs) of the object and the background. The probability distribution of the background is computed from the background window, which has the same number of pixels within the candidate object region. Experiments for various IR images show that the proposed method is proper to segment out the interesting object in IR image sequences. To evaluate performance of proposed segmentation method, we compare other segmentation methods.

Threshold Selection Method in Gray Images Based on Interval-Valued Fuzzy Sets (구간값 퍼지집합을 이용한 그레이 영상에서의 임계값 선택방법)

  • Son, Chang-S.;Chung, Hwan-M.;Seo, Suk-T.;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.4
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    • pp.443-450
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    • 2007
  • In this paper, we propose a novel threshold selection method based on statistical information on gray-levels of given images and interval-valued fuzzy sets. In the proposed threshold selection method, the interval-valued fuzzy set is used to represent more definitely the relationship between a pixel and its belonging region, that is, the object and the background. Also the statistical information on gray-level is used to determine the rules and partitions of interval-valued fuzzy sets. To show the validity of the proposed method, we compared the performance of the proposed with those of conventional methods such as Otsu's method, Huang and Wang's method applied to 5 test images with various types of histograms.

Moving Object Detection using Gaussian Pyramid based Subtraction Images in Road Video Sequences (가우시안 피라미드 기반 차영상을 이용한 도로영상에서의 이동물체검출)

  • Kim, Dong-Keun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.12
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    • pp.5856-5864
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    • 2011
  • In this paper, we propose a moving object detection method in road video sequences acquired from a stationary camera. Our proposed method is based on the background subtraction method using Gaussian pyramids in both the background images and input video frames. It is more effective than pixel based subtraction approaches to reduce false detections which come from the mis-registration between current frames and the background image. And to determine a threshold value automatically in subtracted images, we calculate the threshold value using Otsu's method in each frame and then apply a scalar Kalman filtering to the threshold value. Experimental results show that the proposed method effectively detects moving objects in road video images.

Objective Measurement of Water Repellency of Fabric Using Image Analysis (I) - Methodology of Image Processing -

  • Jeong Young Jin;Jang Jinho
    • Fibers and Polymers
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    • v.6 no.2
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    • pp.162-168
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    • 2005
  • A methodology for the objective evaluation of water repellency is studied using image analysis of the sprayed pattern on woven fabrics according to a standard spray test (AATCC Test Method 22-2001). The wet area ratio obtained from the spray standard test ranking is found to be exponentially related with its water repellency rating. Mean filtering is used to remove the effect of weave texture and the transmitted light through interyarn spaces. The ring frame of the instrument and wet region are recognized using Otsu thresholding technique. And Hough transform and outline operation are used to obtain the size and position of the ring frame. The objective assessment of the water repellency using image processing can reduce unnecessary confusion in the subjective determination of the water repellency.

A Study on the Post Processing of Flash Boiling Spray Image from Shadowgraphy (감압비등 분무의 역광이미지 후처리 기법에 관한 연구)

  • Hyunchang Lee
    • Journal of ILASS-Korea
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    • v.29 no.2
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    • pp.91-97
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    • 2024
  • When investigating the droplet, spray, and impact of liquid on a solid plate, backlight imaging has been widely used to understand these phenomena. However, some previous studies have suffered from poor image quality. In this study, various combinations of image processing algorithms, such as white image correction, histogram equalization, CLAHE, Otsu's binarization, and multi-Otsu's binarization, have been applied to flash boiling spray images to enhance image quality for qualitative observation and semi-quantitative spray angle evaluation. To acquire images with high contrast for qualitative observation, applying CLAHE was effective, making small droplets and detailed shapes of the jet noticeable. However, when images were averaged to determine spray angle or penetration length based on intensity, this method induced artifact unphysical patterns, thus requiring careful consideration. Based on the algorithm proposed in this study, the spray angle variation according to injection pressure and temperature has been calculated, showing a reasonable trend.

Comparison of Blooming Artifact Reduction Using Image Segmentation Method in CT Image (CT영상에서 이미지 분할기법을 적용한 Blooming Artifact Reduction 비교 연구)

  • Kim, Jung-Hun;Park, Ji-Eun;Park, Yu-Jin;Ji, In-Hee;Lee, Jong-Min;Cho, Jin-Ho
    • Journal of Biomedical Engineering Research
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    • v.38 no.6
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    • pp.295-301
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    • 2017
  • In this study, We subtracted the calcification blooming artifact from MDCT images of coronary atherosclerosis patients and verified their accuracy and usefulness. We performed coronary artery calcification stenosis phantom and a program to subtract calcification blooming artifact by applying 8 different image segmentation method (Otsu, Sobel, Prewitt, Canny, DoG, Region Growing, Gaussian+K-mean clustering, Otsu+DoG). As a result, In the coronary artery calcification stenosis phantom with the lumen region 5 mm the calcification blooming artifact was subtracted in the application of the mixture of Gaussian filtering and K- Clustering algorithm, and the value was close to the actual calcification region. These results may help to accurately diagnose coronary artery calcification stenosis.