• Title/Summary/Keyword: morphological segmentation

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Research on Water Edge Extraction in Islands from GF-2 Remote Sensing Image Based on GA Method

  • Bian, Yan;Gong, Yusheng;Ma, Guopeng;Duan, Ting
    • Journal of Information Processing Systems
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    • v.17 no.5
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    • pp.947-959
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    • 2021
  • Aiming at the problem of low accuracy in the water boundary automatic extraction of islands from GF-2 remote sensing image with high resolution in three bands, new water edges automatic extraction method in island based on GF-2 remote sensing images, genetic algorithm (GA) method, is proposed in this paper. Firstly, the GA-OTSU threshold segmentation algorithm based on the combination of GA and the maximal inter-class variance method (OTSU) was used to segment the island in GF-2 remote sensing image after pre-processing. Then, the morphological closed operation was used to fill in the holes in the segmented binary image, and the boundary was extracted by the Sobel edge detection operator to obtain the water edge. The experimental results showed that the proposed method was better than the contrast methods in both the segmentation performance and the accuracy of water boundary extraction in island from GF-2 remote sensing images.

Performance Analysis of Cervical Cancer Detection System Using Fusion Based CFICNN Classifier

  • I. Dhurga bai;A. Selvapandian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.10
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    • pp.2943-2965
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    • 2024
  • This paper proposes a fully computer assisted automated cervical cancer detection method using cervical images. This proposed system consist of six modules as Edge detector, image fusion, Gabor transform, feature computation, classification algorithm and segmentation method. The edge pixels show the contrast edge variations of each pixel in cervical image with respect to its corresponding nearby pixels. Hence, these edge pixels are detected using fuzzy logic and then the edge detected cervical images are fused using arithmetic pixel fusion algorithm. This fused cervical image having the pixels in the form of spatial resolution and hence it is need to be converted into multi-format resolution for computing the features from it. The spatial pixels in fused image are converted into multi orientation pixels using Gabor transform and then features are computed from this Gabor image. In this work, Local Binary Pattern (LBP), Grey Level Co-occurrence Matrix (GLCM) and Pixel Intensity Features (PIF) are computed from the Gabor cervical image. These features have been classified by the Cervical Features Incorporated Convolutional Neural Networks (CFICNN) classification algorithm. The modified version of the Visual Geometry Group- Convolutional Neural Networks (VGG-CNN) architecture is called as Cervical Features Incorporated CNN (CFICNN) and it is proposed in this paper for both training and classification process. Finally, the cancer pixels are segmented using morphological operations based segmentation algorithm. The Guanacaste Dataset (GD) and Kaggle Dataset (KD) are used for estimating performance efficiency.

Efficient Contour Coding for Segmentation-Based Image Coding (분할 기반 영상 부호화를 위한 효율적 윤곽선 부호화)

  • Kim, Gi-Seok;Park, Young-Sik;Song, Kun-Woen;Chung, Eui-Yoon;Kim, Yong-Suk;Ha, Yeong-Ho
    • 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.

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Automated Cell Counting Method for HeLa Cells Image based on Cell Membrane Extraction and Back-tracking Algorithm (세포막 추출과 역추적 알고리즘 기반의 HeLa 세포 이미지 자동 셀 카운팅 기법)

  • Kyoung, Minyoung;Park, Jeong-Hoh;Kim, Myoung gu;Shin, Sang-Mo;Yi, Hyunbean
    • 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.

Intensity Correction of 3D Stereoscopic Images Using Binarization-Based Region Segmentation (이진화기반 영역분할을 이용한 3D입체영상의 밝기보정)

  • Kim, Sang-Hyun;Kim, Jeong-Yeop
    • 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.

Lung and Airway Segmentation using Morphology Information and Spline Interpolation in Lung CT Image (흉부 CT 영상의 형태학적 정보 및 Spline 보간법을 이용한 폐 및 기관지 분할 알고리즘)

  • Cho, Joon-Ho;Kim, Jung-Chul
    • 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.

Automatic Brain Segmentation for 3D Visualization and Analysis of MR Image Sets (MR영상의 3차원 가시화 및 분석을 위한 뇌영역의 자동 분할)

  • Kim, Tae-Woo
    • 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.

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Automated radiation field edge detection in portal image using optimal threshold value (최적 문턱치 설정을 이용한 포탈영상에서의 자동 에지탐지 기법에 관한 연구)

  • 허수진
    • 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.

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Character Segmentation from Shipping Container Image using Morphological Operation (형태학적 연산을 이용한 운송 컨테이너 영상의 문자 분할)

  • 김낙빈
    • 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.

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Two new Phyllopodopsyllus (Copepoda, Harpacticoida) from Korean marine interstitial

  • Karanovic, Tomislav
    • 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.