• Title/Summary/Keyword: Region Extraction

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Automatic Extraction of Chromosome Image Samples for the Karyotype Analysis (핵형분석을 위한 염색체 영상 표본의 자동 추출)

  • Chang, Yong-Hoon;Lee, Kwon-Soon;Jeon, Gye-Rok
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.661-663
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    • 1995
  • Chromosome analysis is an important and difficult task for clinical diagnosis for mutagen dosimetry, and for biological research. It is expensive, time consuming and imprecise when performed manually. Efforts to automate some or all of the procedures have continued for more than 30 years, with only limited success. An acquiring sample from chromosome group is not solved with automatic method. It is still performed by user. This paper represents the method of an automatic chromosome sample extraction which based on region splitting, and scan converted method.

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Image segmentation and line segment extraction for 3-d building reconstruction

  • Ye, Chul-Soo;Kim, Kyoung-Ok;Lee, Jong-Hun;Lee, Kwae-Hi
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.59-64
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    • 2002
  • This paper presents a method for line segment extraction for 3-d building reconstruction. Building roofs are described as a set of planar polygonal patches, each of which is extracted by watershed-based image segmentation, line segment matching and coplanar grouping. Coplanar grouping and polygonal patch formation are performed per region by selecting 3-d line segments that are matched using epipolar geometry and flight information. The algorithm has been applied to high resolution aerial images and the results show accurate 3-d building reconstruction.

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AUTOMATIC BUILDING EXTRACTION BASED ON MULTI-SOURCE DATA FUSION

  • Lu, Yi Hui;Trinder, John
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.248-250
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    • 2003
  • An automatic approach and strategy for extracting building information from aerial images using combined image analysis and interpretation techniques is described in this paper. A dense DSM is obtained by stereo image matching. Multi-band classification, DSM, texture segmentation and Normalised Difference Vegetation Index (NDVI) are used to reveal building interest areas. Then, based on the derived approximate building areas, a shape modelling algorithm based on the level set formulation of curve and surface motion has been used to precisely delineate the building boundaries. Data fusion, based on the Dempster-Shafer technique, is used to interpret simultaneously knowledge from several data sources of the same region, to find the intersection of propositions on extracted information derived from several datasets, together with their associated probabilities. A number of test areas, which include buildings with different sizes, shape and roof colour have been investigated. The tests are encouraging and demonstrate that the system is effective for building extraction, and the determination of more accurate elevations of the terrain surface.

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Extraction of high thermally stable and nanofibrous chitin from Cicada (Cicadoidea)

  • MOL, Abbas;KAYA, Murat;MUJTABA, Muhammad;AKYUZ, Bahar
    • Entomological Research
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    • v.48 no.6
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    • pp.480-489
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    • 2018
  • Due to the increasing interest in natural biopolymers including chitin, the exploitation of economic and easily accessible chitin sources with good physicochemical properties is nowadays required. In view of this fact, in the current study chitin was extracted and physicochemically characterized from six Cicadas (Hemiptera: Homoptera: Cicadoidea) species collected from Mediterranean region of Turkey (2014-15). Chitin was extracted using a classic extraction method that includes acid and base treatment. TGA results revealed a remarkable increase ($410-412^{\circ}C$) for all the six Cicada species compared to other chitin samples extracted from various sources. For all of the six selected species the chitin contents on the dry basis were determined as 6.7% for Cicadatra atra, 5.51% for C. hyalina, 8.84% for C. platyptera, 4.97% for Cicada lodosi, 6.49% for C. mordoganensis, and 5.88% for Cicadetta tibialis. The surface morphology of chitin isolates from Cicada species was observed to consist of nanofibers and nanopores.

Hemisection and Endodontic Treatment of First Molar Tooth and Mandibular Fracture Repair in a Dog

  • Kim, Gyu-min;Kim, Jury;Bae, Hyeon-a;Kim, Nam-soo;Ji, Dong-Beom
    • Journal of Veterinary Clinics
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    • v.36 no.2
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    • pp.106-108
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    • 2019
  • This clinical report describes hemisection and endodontic treatment of first molar tooth and mandible fracture repair in a dog. A 10 years old spayed female shih-tzu was diagnosed as left mandibular fracture by oral examination and dental radiography. First, partial odontectomy of mesial root of mandibular first molar placed in fracture line was performed, and then endodontic treatment of distal root and bone graft in extraction site was performed. Thereafter the fracture region was fixed with interdental wiring and acryl resin splint. Mandibular fracture site was healed without any complications, observed for 19 weeks follow-up period. Upon this result, this case is proving that fractured mandible can be treated successfully with hemisection followed by bone graft, interdental wiring and acryl resin splint to preserve the remaining tooth for mastication rather than tooth extraction.

Skin Color Based Facial Features Extraction

  • Alom, Md. Zahangir;Lee, Hyo Jong
    • Annual Conference of KIPS
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    • 2011.11a
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    • pp.351-354
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    • 2011
  • This paper discusses on facial features extraction based on proposed skin color model. Different parts of face from input image are segmented based on skin color model. Moreover, this paper also discusses on concept to detect the eye and mouth position on face. A height and width ratio (${\delta}=1.1618$) based technique is also proposed to accurate detection of face region from the segmented image. Finally, we have cropped the desired part of the face. This exactly exacted face part is useful for face recognition and detection, facial feature analysis and expression analysis. Experimental results of propose method shows that the proposed method is robust and accurate.

Handwritten Image Segmentation by the Modified Area-based Region Selection Technique (변형된 면적기반영역선별 기법에 의한 문자영상분할)

  • Hwang Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.5 s.311
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    • pp.30-36
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    • 2006
  • In this paper, a new type of written image segmentation based on relative comparison of region areas is proposed. The original image is composed of two distinctive regions; information and background. Compared with this binary original image, the observed one is the gray scale which is represented with complex regions with speckles and noise due to degradation or contamination. For applying threshold or statistical approach, there occurs the region-deformation problem in the process of binarization. At first step, the efficient iterated conditional mode (ICM) which takes the lozenge type block is used for regions formation into the binary image. Secondly the information region is estimated through selecting action and restored its primary state. Not only decision of the attachment to a region but also the calculation of the magnitude of its area are carried on at each current pixel iteratively. All region areas are sorted into a set and selected through the decision parameter which is obtained statistically. Our experiments show that these approaches are effective on ink-rubbed copy image (拓本 'Takbon') and efficient at shape restoration. Experiments on gray scale image show promising shape extraction results, comparing with the threshold-segmentation and conventional ICM method.

Raising Visual Experience of Soccer Video for Mobile Viewers (이동형 단말기 사용자를 위한 축구경기 비디오의 시청경험 향상 방법)

  • Ahn, Il-Koo;Ko, Jae-Seung;Kim, Won-Jun;Kim, Chang-Ick
    • Journal of KIISE:Computing Practices and Letters
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    • v.13 no.3
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    • pp.165-178
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    • 2007
  • The recent progress in multimedia signal processing and transmission technologies has contributed to the extensive use of multimedia devices to watch sports games with small LCD panel. However, the most of video sequences are captured for normal viewing on standard TV or HDTV, for cost reasons, merely resized and delivered without additional editing. This may give the small-display-viewers uncomfortable experiences in understanding what is happening in a scene. For instance, in a soccer video sequence taken by a long-shot camera techniques, the tiny objects (e.g., soccer ball and players) may not be clearly viewed on the small LCD panel. Moreover, it is also difficult to recognize the contents of the scorebox which contains the elapsed time and scores. This renuires intelligent display technique to provide small-display-viewers with better experience. To this end, one of the key technologies is to determine region of interest (ROI) and display the magnified ROI on the screen, where ROI is a part of the scene that viewers pay more attention to than other regions. Examples include a region surrounding a ball in long-shot and a scorebox located in the comer of each frame. In this paper, we propose a scheme for raising viewing experiences of multimedia mobile device users. Instead of taking generic approaches utilizing visually salient features for extraction of ROI in a scene, we take domain-specific approach to exploit unique attributes of the soccer video. The proposed scheme consists of two modules: ROI determination and scorebox extraction. The experimental results show that the proposed scheme offers useful tools for intelligent video display on multimedia mobile devices.

An Extraction Method of Number Plates for Various Vehicles Using Digital Signal Analysis Processing Techniques (디지털 신호 분석 기법을 이용한 다양한 번호판 추출 방법)

  • Yang, Sun-Ok;Jun, Young-Min;Jung, Ji-Sang;Ryu, Sang-Hwan
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.3
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    • pp.12-19
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    • 2008
  • Detection of a number plate consists of three stages; division of a number plate, extraction of each character from the plate, recognition of the characters. Among of these three states, division stage of a number plate is the most important part and also the most time-consuming state. This paper suggests an effective region extraction method of a number plate for various images obtained from unmanned inspection systems of illegal parking violation, especially when we have to consider the diverse surrounding environments of roads. Our approaching method detects each region by investigating the characteristics in changes of brightness and intensity between the background part and character part, and the characteristics on character parts such as the sizes, heights, widths, and distance in between two characters. The method also divides a number plate into different types of the plate. This research can solve the number plate region detection failure problems caused by plate edge damages not only for Korean domestic number plates but also for new European style number plates. The method also reduces the time consumption by processing the detection in real-time, therefore, it can be used as a practical solution.

Development of Learning Algorithm using Brain Modeling of Hippocampus for Face Recognition (얼굴인식을 위한 해마의 뇌모델링 학습 알고리즘 개발)

  • Oh, Sun-Moon;Kang, Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.55-62
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    • 2005
  • In this paper, we propose the face recognition system using HNMA(Hippocampal Neuron Modeling Algorithm) which can remodel the cerebral cortex and hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature-vector of the face images very fast and construct the optimized feature each image. The system is composed of two parts. One is feature-extraction and the other is teaming and recognition. In the feature extraction part, it can construct good-classified features applying PCA(Principal Component Analysis) and LDA(Linear Discriminants Analysis) in order. In the learning part, it cm table the features of the image data which are inputted according to the order of hippocampal neuron structure to reaction-pattern according to the adjustment of a good impression in the dentate gyrus region and remove the noise through the associate memory in the CA3 region. In the CA1 region receiving the information of the CA3, it can make long-term memory learned by neuron. Experiments confirm the each recognition rate, that are face changes, pose changes and low quality image. The experimental results show that we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to existing methods.