• Title/Summary/Keyword: Automatic Extraction Algorithm

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Automatic Extraction of Canine Cataract Area with Fuzzy Clustering (퍼지 클러스터링을 이용한 반려견의 백내장 영역 자동 추출)

  • Kim, Kwang Baek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.11
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    • pp.1428-1434
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    • 2018
  • Canine cataract is developed with aging and can cause the blindness or surgical treatment if not treated timely. In this paper, we propose a method for extracting cataract suspicious areas automatically with FCM(Fuzzy C_Means) algorithm to overcome the weakness of previously attempted ART2 based method. The proposed method applies the fuzzy stretching technique and the Max-Min based average binarization technique to the dog eye images photographed by simple devices such as mobile phones. After applying the FCM algorithm in quantization, we apply the brightness average binarization method in the quantized region. The two binarization images - Max-Min basis and brightness average binarization - are ANDed, and small noises are removed to extract the final cataract suspicious areas. In the experiment with 45 dog eye images with canine cataract, the proposed method shows better performance in correct extraction rate than the ART2 based method.

Analysis of Fish Activity in Relation to Feeding Events Using Infrared Cameras (적외선 카메라를 활용한 급이 유무에 따른 어류 활동성 분석)

  • Roh, Tae Kyoung;Ha, Sang Hyun;Kim, Ki Hwan;Kang, Young Jin;Jeong, Seok Chan
    • The Journal of Information Systems
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    • v.32 no.4
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    • pp.137-147
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    • 2023
  • Purpose The domestic aquaculture industry in South Korea utilizes both formulated feeds and live feeds for the cultivation of fish. While nutrient-rich live feeds, particularly using fry, have been preferred since the past, formulated feeds are gaining attention due to issues related to overfishing and environmental concerns. Formulated feeds are advantageous for storage and supply but require a sustained feeding regimen due to the comparatively slower growth rate compared to live feeds. As the aging population in rural areas leads to a shortage of labor, automated feeding systems are increasingly being adopted in aquaculture facilities. To enhance the efficiency of such systems, it is crucial to quantitatively analyze the behavioral changes in fish based on the presence or absence of feed. Design/methodology/approach In the study, RGB cameras and infrared cameras were used to analyze fish activity according to feeding, and an outline extraction algorithm was applied to analyze the differences resulting from this. Findings Unlike RGB cameras, infrared cameras are more suitable for analyzing underwater fish activity as they convert objects' thermal energy into images. It was observed that Canny, Sobel, and Prewitt filters showed the most distinct identification of fish activity.

A Effective Method for Feature Detection and Enhancement in Fingerprint Images (지문의 특징 검출 및 향상을 위한 전처리 기법 연구)

  • Yang, Ryong;No, Jung-Seok;Lee, Sang-Bum
    • Journal of the Korea Computer Industry Society
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    • v.3 no.12
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    • pp.1775-1784
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    • 2002
  • Fingerprint recognition technology is used in many biometrics field accordingly essential feature of fingerprint image and the study is progressing. However development is not perfect in performance of the fingerprint recognition and application of the usual life. In the paper, we study various necessity of preprocessing according to algorithm and circumstances of authentication system in automatic information machine. We prove that system circumstance and optation of fingerprints image effectively is the important factor by using optical fingerprint input device and scanning the fingerprint in ID card. And then we present correct and fast computation method for improving image and feature extraction of fingerprint. Also we study effective algorithm implementation of total system.

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Robust Extraction of Lean Tissue Contour From Beef Cut Surface Image

  • Heon Hwang;Lee, Y.K.;Y.r. Chen
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1996.06c
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    • pp.780-791
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    • 1996
  • A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

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A Study of Automatic Vehicle Control by Image Processing (화상처리 기술을 이용한 자동차 교통 제어에 관한 연구)

  • Choe, Hyeong-Jin;Yang, Hae-Sul
    • The Transactions of the Korea Information Processing Society
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    • v.1 no.3
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    • pp.418-426
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    • 1994
  • Auto Navigation System is to provide a vehicle driver with more driving information by developing a computer-based system which supports advanced knowledge to a vehicle driving automation system and a driver. In this paper, we propose a new algorithm for the extraction of passing car which removes a background region using a series of images. First, we generate two difference images from three original images by getting the difference values between every two of them in sequence. Second, we generate two mask images from the two difference images. Finally, we extract passing car using the one original image and the two mask images. Using this algorithm we can extract the moving object in the outdoors.

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Automatic Extraction of Road Network using GDPA (Gradient Direction Profile Algorithm) for Transportation Geographic Analysis

  • Lee, Ki-won;Yu, Young-Chul
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.775-779
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    • 2002
  • Currently, high-resolution satellite imagery such as KOMPSAT and IKONOS has been tentatively utilized to various types of urban engineering problems such as transportation planning, site planning, and utility management. This approach aims at software development and followed applications of remotely sensed imagery to transportation geographic analysis. At first, GDPA (Gradient Direction Profile Algorithm) and main modules in it are overviewed, and newly implemented results under MS visual programming environment are presented with main user interface, input imagery processing, and internal processing steps. Using this software, road network are automatically generated. Furthermore, this road network is used to transportation geographic analysis such as gamma index and road pattern estimation. While, this result, being produced to do-facto format of ESRI-shapefile, is used to several types of road layers to urban/transportation planning problems. In this study, road network using KOMPSAT EOC imagery and IKONOS imagery are directly compared to multiple road layers with NGI digital map with geo-coordinates, as ground truth; furthermore, accuracy evaluation is also carried out through method of computation of commission and omission error at some target area. Conclusively, the results processed in this study is thought to be one of useful cases for further researches and local government application regarding transportation geographic analysis using remotely sensed data sets.

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Nucleus Segmentation and Recognition of Uterine Cervical Pap-Smears using Enhanced Fuzzy ART Algorithm (개선된 퍼지 ART 알고리즘을 이용한 자궁 경부 세포진 핵 분할 및 인식)

  • Kim, Kwang-Baek
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.519-524
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    • 2006
  • Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the fuzzy grey morphology operation. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The enhanced fuzzy ART algorithm is used to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.

The Verification of Accuracy of 3D Body Scan Data - Focused on the Cyberware WB4 Whole Body Scanner - (3차원 인체 스캔 데이터의 정확도 검증에 관한 연구 - Cyberware의 WB4 스캐너를 중심으로 -)

  • Park, Sun-Mi;Nam, Yun-Ja
    • Journal of the Korea Fashion and Costume Design Association
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    • v.14 no.1
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    • pp.81-96
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    • 2012
  • The purpose of this study is to provide fundamental information for standardization of 3D body measurement. This research analyzes errors occurring in the process of extracting body size from 3D body scan data. First, as a result of analyzing basic state of the 3D body scanner's calibration, the point number of each section was almost the same, while the right and left as well as the front and back coordinates of the center of gravity are not, showing unstable data. Nevertheless, the latter does not influence on the size of cylinder such as width and circumference. Next, we analyzed point coordinates variations of scan data on a mannequin nude by life casting. The result was great deflection in case of complicated or horizontal sections including the reference point beyond proper distance from centers of four cameras. In case of the mannequin's size, accuracy proves comparatively high in that measurement errors in height, width, depth, and length dimension occurred all within allowable errors, only except chest depth, while there were a lot of measurement errors in a circumference dimension. Secondly, analysis of accuracy of automatic extraction identification program algorithm presented that a semi-automatic measurement program is better than an automatic measurement program. While both of them ate very acute in parts related to crotch, they are not in armpit related parts. Therefore, in extracting of human body size from 3D scan data, what really matters seems to parts related to armpits.

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Auto-Analysis of Traffic Flow through Semantic Modeling of Moving Objects (움직임 객체의 의미적 모델링을 통한 차량 흐름 자동 분석)

  • Choi, Chang;Cho, Mi-Young;Choi, Jun-Ho;Choi, Dong-Jin;Kim, Pan-Koo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.6
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    • pp.36-45
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    • 2009
  • Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.

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Automatic Target Recognition by selecting similarity-transform-invariant local and global features (유사변환에 불변인 국부적 특징과 광역적 특징 선택에 의한 자동 표적인식)

  • Sun, Sun-Gu;Park, Hyun-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.4
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    • pp.370-380
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    • 2002
  • This paper proposes an ATR (Automatic Target Recognition) algorithm for identifying non-occluded and occluded military vehicles in natural FLIR (Forward Looking InfraRed) images. After segmenting a target, a radial function is defined from the target boundary to extract global shape features. Also, to extract local shape features of upper region of a target, a distance function is defined from boundary points and a line between two extreme points. From two functions and target contour, four global and four local shape features are proposed. They are much more invariant to translation, rotation and scale transform than traditional feature sets. In the experiments, we show that the proposed feature set is superior to the traditional feature sets with respect to the similarity-transform invariance and recognition performance.