• Title/Summary/Keyword: Thresholding Technique

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Development of Automatic Cluster Algorithm for Microcalcification in Digital Mammography (디지털 유방영상에서 미세석회화의 자동군집화 기법 개발)

  • Choi, Seok-Yoon;Kim, Chang-Soo
    • Journal of radiological science and technology
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    • v.32 no.1
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    • pp.45-52
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    • 2009
  • Digital Mammography is an efficient imaging technique for the detection and diagnosis of breast pathological disorders. Six mammographic criteria such as number of cluster, number, size, extent and morphologic shape of microcalcification, and presence of mass, were reviewed and correlation with pathologic diagnosis were evaluated. It is very important to find breast cancer early when treatment can reduce deaths from breast cancer and breast incision. In screening breast cancer, mammography is typically used to view the internal organization. Clusterig microcalcifications on mammography represent an important feature of breast mass, especially that of intraductal carcinoma. Because microcalcification has high correlation with breast cancer, a cluster of a microcalcification can be very helpful for the clinical doctor to predict breast cancer. For this study, three steps of quantitative evaluation are proposed : DoG filter, adaptive thresholding, Expectation maximization. Through the proposed algorithm, each cluster in the distribution of microcalcification was able to measure the number calcification and length of cluster also can be used to automatically diagnose breast cancer as indicators of the primary diagnosis.

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A Study on Clustering and Color Difference Evaluation of Color Image using HSV Color Space (HSV색공간을 이용한 칼라화상의 클러스터링 및 색차평가에 관한 연구)

  • Kim, Young-Il
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.2
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    • pp.20-27
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    • 1998
  • This paper describes color clustering method based on color difference in the uniform Munsell color space obtained from hue, saturation, and value. The proposed method operates in the uniform HSV color space which is approximated using ${L^*}{a^*}{b^*}$ coordinate system based on the RGB inputs. A clustering and color difference evaluation are proposed by thresholding NBS unit which is likely to Balinkin color difference equation. Region segmentation and isolation process are carried out ISO DATA algorithm which is a self iterative clustering technique. Through the clustering of 2 input images according to the threshold value, satisfactory results are obtained. So, in conclusion, it is possible to extract result of better region segmentation using human color perception of the objects.

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A Comparative Study of Wetland Change Detection Techniques Using Post-Classification Comparison and Image Differencing on Landsat-5 TM Data (랜�V-5호(號) TM 데이타를 이용(利用)한 구분후(區分后) 비교(比較) 및 영상대차(映像對差)의 습지대(濕地帶) 변화(變化) 탐지(探知) 기법(技法)에 관(關)한 비교연구(比較硏究))

  • Choung, Song Hak;Ulliman, Joseph J.
    • Journal of Korean Society of Forest Science
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    • v.81 no.4
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    • pp.346-356
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    • 1992
  • The extensive Snake River floodplain in Northwest United States has experienced major changes in water channels and vegetation types due to floodings. To detect the change of wetland cover-types for the period of 1985 and 1988, post-classification comparison and image differencing change detection techniques were evaluated using Landsat-5 TM digital data. Differenced infrared-band images indicated better accuracy indices than any visible-band images. A thresholding technique was applied to identify the change and no change categories from the transformed images produced by image differencing. The problems in using different accuracy indices, including the Kappa coefficient of agreement, overall accuracy, producer's accuracy, user's accuracy, and average accuracy(based on both the producer's and user's accuracy approaches) in determining an optimal threshold level, were examined.

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Development of an Automatic Seeding System Using Machine Vision for Seed Line-up of Cucurbitaceous Vegetables (기계시각을 이용한 박과채소 종자 정렬파종시스템 개발)

  • Kim, Dong-Eok;Cho, Han-Keun;Chang, Yu-Seob;Kim, Jong-Goo;Kim, Hyeon-Hwan;Son, Jae-Ryoung
    • Journal of Biosystems Engineering
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    • v.32 no.3
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    • pp.179-189
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    • 2007
  • Most of the seeds of cucurbitaceous rootstock species used for grafting were mainly sown by hand. This study was carried out to develop an on-line discriminating algorithm of seed direction using machine vision and an automatic seeding system. The seeding system was composed of a supplying device, feeding device, machine vision system, reversing device, seeding device and system control section. Machine vision was composed of a color CCD camera, frame grabber, image inspection chamber, lighting and personal computer. The seed image was segmented into a region of seed part and background part using thresholding technique in which H value of HSI color coordinate system. A seed direction was discriminated by comparing position between the center of circumscribed rectangle to a seed and the center of seed image. It took about 49ms to identify and redirect seed. Line-up status of seed was good the more than 95% of a sowed seed. Seeding capacity of this system was shown to be 10,140 grains per hour, which is three times faster than that of a typical worker.

Object Detection Algorithm in Sea Environment Based on Frequency Domain (주파수 도메인에 기반한 해양 물표 검출 알고리즘)

  • Park, Ki-Tae;Jeong, Jong-Myeon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.4
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    • pp.494-499
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    • 2012
  • In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

A Study on the Extraction of Road & Vehicles Using Image Processing Technique (영상처리 기술을 이용한 도로 및 차량 추출 기법에 관한 연구)

  • Ga, Chill-O;Byun, Young-Gi;Yu, Ki-Yun;Kim, Yong-Il
    • Journal of Korean Society for Geospatial Information Science
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    • v.13 no.4 s.34
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    • pp.3-9
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    • 2005
  • The extraction of traffic information based on image processing is under broad research recently because the method based on image processing takes less cost and effort than the traditional method based on physical equipment. The main purpose of the algorithm based on image processing is to extract vehicles from an image correctly. Before the extraction, the algorithm needs the pre-processing such as background subtraction and binary image thresholding. During the pre-processing much noise is brought about because roadside tree and passengers in the sidewalk as well as vehicles are extracted as traffic flow. The noise undermines the overall accuracy of the algorithm. In this research, most of the noise could be removed by extracting the exact road area which does not include sidewalk or roadside tree. To extract the exact road area, traffic lanes in the image were used. Algorithm speed also increased. In addition, with the ratio between the sequential images, the problem caused by vehicles' shadow was minimized.

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Implementation of an Effective Human Head Tracking System Using the Ellipse Modeling and Color Information (타원 모델링과 칼라정보를 이용한 효율적인 머리 추적 시스템 구현)

  • Park, Dong-Sun;Yoon, Sook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.6
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    • pp.684-691
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    • 2001
  • In this paper, we design and implement a system which recognizes and tracks a human head on a sequence of images. In this paper, the color of the skin and ellipse modeling is used as feature vectors to recognize the human head. And the modified time-varying edge detection method and the vertical projection method is used to acquire regions of the motion from images with very complex backgrounds. To select the head from the acquired candidate regions, the process for thresholding on the basis of the I-component of YIQ color information and mapping with ellipse modeling is used. The designed system shows an excellent performance in the cases of the rotated heads, occluded heads, and tilted heads as well as in the case of the normal up-right heads. And in this paper, the combinational technique of motion-based tracking and recognition-based tracking is used to track the human head exactly even though the human head moves fast.

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Implementation of Commercial IWB Interface using Image Processing (영상처리를 이용한 상업용 전자칠판의 인터페이스 구현)

  • Ko, Eunsang;Rhee, Yang Won;Lee, Chang Woo
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.6
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    • pp.19-24
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    • 2012
  • In this paper we introduce a commercial interactive whiteboard (IWB) system named ImSensorTouch by ImSensor Inc. Using this interface system, we can control our computer through the interactive whiteboard screen just by touching it with your finger or a pen. The interface interacts with Windows operating system (OS) and is adaptable to changes of surroundings especially temperature, and illumination condition. The proposed system calculates the difference between a reference image and a current image captured by a camera in the optical receptive field. And the position making the difference is used to generate the position on Windows screen. Then, we send a mouse event on the position to Windows OS. We have implemented the system using a critical section(CS) with two threads for the reference frame update process in which an adaptive thresholding technique is periodically exploited to get reliable result. We expect the system is competitive and promises a bright future in the IWB market.

Object Width Measurement System Using Light Sectioning Method (광절단법을 이용한 물체 크기 측정 시스템)

  • Lee, Byeong-Ju;Kang, Hyun-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.3
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    • pp.697-705
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    • 2014
  • This paper presents a vision based object width measurement method and its application where the light sectioning method is employed. The target object for measurement is a tread, which is the most outside component of an automobile tire. The entire system applying the measurement method consists of two processes, i.e. a calibration process and a detection process. The calibration process is to identify the relationships between a camera plane and a laser plane, and to estimate a camera lens distortion parameters. As the process requires a test pattern, namely a jig, which is elaborately manufactured. In the detection process, first of all, the region that a laser light illuminates is extracted by applying an adaptive thresholding technique where the distribution of the pixel brightness is considered to decide the optimal threshold. Then, a thinning algorithm is applied to the region so that the ends and the shoulders of a tread are detected. Finally, the tread width and the shoulder width are computed using the homography and the distortion coefficients obtained by the calibration process.

Development of Statistical/Probabilistic-Based Adaptive Thresholding Algorithm for Monitoring the Safety of the Structure (구조물의 안전성 모니터링을 위한 통계/확률기반 적응형 임계치 설정 알고리즘 개발)

  • Kim, Tae-Heon;Park, Ki-Tae
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.20 no.4
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    • pp.1-8
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    • 2016
  • Recently, buildings tend to be large size, complex shape and functional. As the size of buildings is becoming massive, the need for structural health monitoring(SHM) technique is ever-increasing. Various SHM techniques have been studied for buildings which have different dynamic characteristics and are influenced by various external loads. Generally, the visual inspection and non-destructive test for an accessible point of structures are performed by experts. But nowadays, the system is required which is online measurement and detect risk elements automatically without blind spots on structures. In this study, in order to consider the response of non-linear structures, proposed a signal feature extraction and the adaptive threshold setting algorithm utilized to determine the abnormal behavior by using statistical methods such as control chart, root mean square deviation, generalized extremely distribution. And the performance of that was validated by using the acceleration response of structures during earthquakes measuring system of forced vibration tests and actual operation.