• Title/Summary/Keyword: image thinning

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3D image processing using laser slit beam and CCD camera (레이저 슬릿빔과 CCD 카메라를 이용한 3차원 영상인식)

  • 김동기;윤광의;강이석
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.40-43
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    • 1997
  • This paper presents a 3D object recognition method for generation of 3D environmental map or obstacle recognition of mobile robots. An active light source projects a stripe pattern of light onto the object surface, while the camera observes the projected pattern from its offset point. The system consists of a laser unit and a camera on a pan/tilt device. The line segment in 2D camera image implies an object surface plane. The scaling, filtering, edge extraction, object extraction and line thinning are used for the enhancement of the light stripe image. We can get faithful depth informations of the object surface from the line segment interpretation. The performance of the proposed method has demonstrated in detail through the experiments for varies type objects. Experimental results show that the method has a good position accuracy, effectively eliminates optical noises in the image, greatly reduces memory requirement, and also greatly cut down the image processing time for the 3D object recognition compared to the conventional object recognition.

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Development of Classification System for Thermal Comfort Behavior of Pigs by Image Processing and Neural Network (영상처리와 인공신경망을 이용한 돼지의 체온조절행동 분류 시스템 개발)

  • 장동일;임영일;장홍희
    • Journal of Biosystems Engineering
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    • v.24 no.5
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    • pp.431-438
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    • 1999
  • The environmental control based on interactive thermoregulatory behavior for swine production has many advantages over the conventional temperature-based control methods. Therefore, this study was conducted to compare various feature selection methods using postural images of growing pigs under various environmental conditions. A color CCD camera was used to capture the behavioral images which were then modified to binary images. The binary images were processed by thresholding, edge detection, and thinning techniques to separate the pigs from their background. Following feature were used for the input patterns to the neural network ; \circled1 perimeter, \circled2 area, \circled3 Fourier coefficients (5$\times$5), \circled4 combination of (\circled1 + \circled2), \circled5 combination of (\circled1 + \circled3), \circled6 combination of (\circled2 + \circled3), and \circled7 combination of (\circled1 + \circled2 + \circled3). Using the above each input pattern, the neural network could classify training images with the success rates of 96%, 96%, 96%, 100%, 100%, 96%, 100%, and testing images with those of 88%, 86%, 93%, 96%, 91%, 90%, 98%, respectively. Thus, the combination of perimeter, area and Fourier coefficients of the thinning images as neural network features gave the best performance (98%) in the behavioral classification.

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License Plate Recognition System Using Artificial Neural Networks

  • Turkyilmaz, Ibrahim;Kacan, Kirami
    • ETRI Journal
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    • v.39 no.2
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    • pp.163-172
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    • 2017
  • A high performance license plate recognition system (LPRS) is proposed in this work. The proposed LPRS is composed of the following three main stages: (i) plate region determination, (ii) character segmentation, and (iii) character recognition. During the plate region determination stage, the image is enhanced by image processing algorithms to increase system performance. The rectangular license plate region is obtained using edge-based image processing methods on the binarized image. With the help of skew correction, the plate region is prepared for the character segmentation stage. Characters are separated from each other using vertical projections on the plate region. Segmented characters are prepared for the character recognition stage by a thinning process. At the character recognition stage, a three-layer feedforward artificial neural network using a backpropagation learning algorithm is constructed and the characters are determined.

Odontogenic myxoma: a case report with recent image modalities

  • Kim Jae-Duk;Kim Kwang-Won;Lim Sung-Hoon
    • Imaging Science in Dentistry
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    • v.34 no.4
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    • pp.199-202
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    • 2004
  • The odontogenic myxoma is an benign, slow growing neoplasm which is of ectomesenchymal origin. This neoplasm occurs almost exclusively in the jaw bones and comprises 0.2% to 17.7% of odontogenic tumors. The odontogenic myxoma may show a wide spectrum of radiographic appearances, unilocular, multilocular radiolucency and a distinct or diffuse border, making the differential diagnosis difficult. We present a case of the odontogenic myxoma in the maxilla with conventional and recent image modalities. Occlusal film revealed a medially extended multilocular lesion with intralesional fine and straight trabeculations from the scalloped margin and buccal expansion and thinning of cortical bone. Computed tomogram revealed lesion showed equivalent density to the muscles in the left maxillary sinus with partial cortical discontinuity of medial wall and the tennis-racket pattern with internal straight trabeculations. MRI revealed intermediate signal intensity on Tl weighted image and high signal intensity on T2 weighted image. In Gd enhanced MR image, the peripheral portions of the lesion were enhanced.

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A Study on the Automatic Classification between Contour Elements and Non-Contour Elements in a Contour Map Image (등고선 지도영상에서의 등고 성분과 비등고 성분의 자동 분리에 관한 연구)

  • 김경훈;김준식
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.4
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    • pp.7-16
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    • 2002
  • En this paper, we propose the algorithm that has analyzed the map Information automatically to extract the contour lines and numbers, symbols from the map image. After converting the input image to binary one, thinned image is obtained by thinning algorithm. The contour elements in the thinned image are classified and the classified elements are analyzed to automatically classify the numbers from symbols. Finally, the broken parts are restored by reconstruction algorithm. The performance of proposed algorithm is verified through the simulation. The proposed one has good performance.

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An Analysis on Face Recognition system of Housdorff Distance and Hough Transform (Housdorff Distance 와 Hough Transform을 적용한 얼굴인식시스템의 분석)

  • Cho, Meen-Hwan
    • Journal of the Korea Computer Industry Society
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    • v.8 no.3
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    • pp.155-166
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    • 2007
  • In this paper, captured face-image was pre-processing, segmentation, and extracting features from thinning by differential operator and minute-delineation. A straight line in slope-intercept form was transformed at the $r-\theta$ domain using Hough Transform, instead of Housdorff distance are extract feature as length, rotation, displacement of lines from thinning line components by differentiation. This research proposed a new approach compare with Hough Transformation and Housdorff Distance for face recognition so that Hough transform is simple and fast processing of face recognition than processing by Housdorff Distance. Rcognition accuracy rate is that Housdorff method is higher than Hough transformation's method.

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A Study on the Strain Analysis by Image Processing Technique (화상처리기법을 이용한 변형율해석에 관한 연구)

  • 백인환;신문교
    • Journal of Advanced Marine Engineering and Technology
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    • v.12 no.4
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    • pp.32-45
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    • 1988
  • The scanning moire method, in which the master grating is replaced by the scanning line of television camera and in which the moire pattern is obtained by thining out some scanning line, is discussed by the sampling theory. It is determined also by the sampling theory that relationship between the fringe pattern. The programs that analyze the strain by the scanning moire method have been developed. For the simulation model in which we are able to calculate analytically the distribution of strains, the scanning moire method is discussed. It is shown that the small strains and the large strains are analyzed from the same picture by the thinning out technique and that the accuracy of analysis is improved by change of the phase in the thinning out technique.

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A Fast Recognition System of Gothic-Hangul using the Contour Tracing (윤곽선 추적에 의한 고딕체 한글의 신속인식에 관한 연구)

  • 정주성;김춘석;박충규
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.37 no.8
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    • pp.579-587
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    • 1988
  • Conventional methods of automatic recognition of Korean characters consist of the thinning processing, the segmentation of connected fundamental phonemes and the recognition of each fundamental character. These methods, however require the thinning processing which is complex and time consuming. Also several noise components make worse effects on the recognition of characters than in the case of no thinning. This paper describes the extraction method of the feature components of Korean fundamental characters of the Gothic Korean letter without the thinning. We regard line-components of the contour which describes the character's external boundary as the feature-components. The line-component includes the directional code, the length and the start point in the image. Each fundamental character is represented by the string of directional codes. Therefore the recognition process is only the string pattern matching. We use the Gothic-hangul in the experiment. The ecognition rate is 92%.

Determination of an Test Condition for IR Thermography to Inspect a Wall-Thinning Defect in Nuclear Piping Components (원전 배관 감육 결함 검사를 위한 IR 열화상시험 조건 결정)

  • Kim, Jin-Weon;Yun, Won-Kyung;Jung, Hyun-Chul;Kim, Kyeong-Suk
    • Journal of the Korean Society for Nondestructive Testing
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    • v.32 no.1
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    • pp.12-19
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    • 2012
  • This study conducted infrared (IR) thermography tests using pipe and plate specimens with artificial wall-thinning defects to find an optimal condition for IR thermography test on the wall-thinned nuclear piping components. In the experiment halogen lamp was used to heat the specimens. The distance between the specimen and the lamp and the intensity of halogen lamp were regarded as experimental parameter. When the distance was set to 1~2 m and the lamp intensity was above 60 % of full power, a single scanning of IR thermography detected all artificial wall-thinning defects, whose minimum dimension was $2{\Theta}=90^{\circ}$, d/t=0.5, and $L/D_o=0.25$, within the pipe of 500 mm in length. Regardless of the distance between the specimen and the lamp, the image of wall-thinning defect in IR thermography became distinctive as the intensity of halogen lamp increased. The detectability of IR thermography was similar for both plate and pipe specimens, but the optimal test condition for IR thermography depended on the type of specimen.

Edge-based range image segmentation method using pseudo reflectance images (의사 밝기 영상을 이용한 에지 기반형 거리 영상 분할)

  • 송호근;김태은;최종수
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.4
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    • pp.111-123
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    • 1996
  • In this paper, a new edge-based segmentation algorithm for range image using pseudo reflectance images (PRIs) is proposed. A model of pseudo reflectance which is useful in analyzing three dimensional scene and objects is introduced and then three PRIs are generated by the model. For generating three PRIs, bels and jain's differential window operator is selected and three different light source directions are determined. Three edge images are extracted from each PRI and a fused (logical ORing) edge image is constructed for the benefit of enhanced edge formation. The final segmentation results of the proposed algoritm are obtained after the processing of thinning, labeling and correcting erroeneous regions with the fused edge image. The good performance of edge detection and segmentation is confirmed via computer simulation with synthetic and real range images.

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