• Title/Summary/Keyword: plane recognition

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Development of Merging Algorithm between 3-D Objects and Real Image for Augmented Reality

  • Kang, Dong-Joong
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.100.5-100
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    • 2002
  • A core technology for implementation of Augmented Reality is to develop a merging algorithm between interesting 3-D objects and real images. In this paper, we present a 3-D object recognition method to decide viewing direction toward the object from camera. This process is the starting point to merge with real image and 3-D objects. Perspective projection between a camera and 3-dimentional objects defines a plane in 3-D space that is from a line in an image and the focal point of the camera. If no errors with perfect 3-D models were introduced in during image feature extraction, then model lines in 3-D space projecting onto this line in the image would exactly lie in this plane. This observa...

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Neural Network Based Camera Calibration and 2-D Range Finding (신경회로망을 이용한 카메라 교정과 2차원 거리 측정에 관한 연구)

  • 정우태;고국원;조형석
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1994.10a
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    • pp.510-514
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    • 1994
  • This paper deals with an application of neural network to camera calibration with wide angle lens and 2-D range finding. Wide angle lens has an advantage of having wide view angles for mobile environment recognition ans robot eye in hand system. But, it has severe radial distortion. Multilayer neural network is used for the calibration of the camera considering lens distortion, and is trained it by error back-propagation method. MLP can map between camera image plane and plane the made by structured light. In experiments, Calibration of camers was executed with calibration chart which was printed by using laser printer with 300 d.p.i. resolution. High distortion lens, COSMICAR 4.2mm, was used to see whether the neural network could effectively calibrate camera distortion. 2-D range of several objects well be measured with laser range finding system composed of camera, frame grabber and laser structured light. The performance of 3-D range finding system was evaluated through experiments and analysis of the results.

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A Characteristics of UV images and PD quantity at Needle-Plane electrodes (침대평판 전극에서의 부분방전량과 자외선 이미지 특성)

  • Shong, Kil-Mok;Kim, Young-Seok;Park, Sang-Taek
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 2009.05a
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    • pp.101-104
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    • 2009
  • In this paper, it's described the techniques for the analysis of corona generated in open live parts of electric facilities. At needle-plane electrodes, when the voltage increased($0{\sim}70kV$, ramping 10kV) using the high voltage generation system(HIPOTRINICS $0{\sim}200kV$, USA), it's generated the partial discharge. There are compared between UV detected image and PD quantity. As these results, UV areas and gains are normalized. And electric facilities are evaluated the 5 steps such as 'good', 'recognition', 'check', 'inspection', 'change(replacement)'.

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Normalization of Face Images Subject to Directional Illumination using Linear Model (선형모델을 이용한 방향성 조명하의 얼굴영상 정규화)

  • 고재필;김은주;변혜란
    • Journal of KIISE:Software and Applications
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    • v.31 no.1
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    • pp.54-60
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    • 2004
  • Face recognition is one of the problems to be solved by appearance based matching technique. However, the appearance of face image is very sensitive to variation in illumination. One of the easiest ways for better performance is to collect more training samples acquired under variable lightings but it is not practical in real world. ]:n object recognition, it is desirable to focus on feature extraction or normalization technique rather than focus on classifier. This paper presents a simple approach to normalization of faces subject to directional illumination. This is one of the significant issues that cause error in the face recognition process. The proposed method, ICR(illumination Compensation based on Multiple Linear Regression), is to find the plane that best fits the intensity distribution of the face image using the multiple linear regression, then use this plane to normalize the face image. The advantages of our method are simple and practical. The planar approximation of a face image is mathematically defined by the simple linear model. We provide experimental results to demonstrate the performance of the proposed ICR method on public face databases and our database. The experimental results show a significant improvement of the recognition accuracy.

Adaptive Vehicle License Plate Recognition System Using Projected Plane Convolution and Decision Tree Classifier (투영면 컨벌루션과 결정트리를 이용한 상태 적응적 차량번호판 인식 시스템)

  • Lee Eung-Joo;Lee Su Hyun;Kim Sung-Jin
    • Journal of Korea Multimedia Society
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    • v.8 no.11
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    • pp.1496-1509
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    • 2005
  • In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

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Recognition and positioning of occuluded objects using polygon segments (다각형 세그먼트를 이용한 겹쳐진 물체의 인식 및 위치 추정)

  • 정종면;문영식
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.5
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    • pp.73-82
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    • 1996
  • In this paper, an efficient algorithm for recognizing and positioning occuluded objects in a two-dimensional plane is presented. Model objects and unknown input image are approximated by polygonal boundaries, which are compactly represented by shape functions of the polygons. The input image is partitioned into measningful segments whose end points are at the locations of possible occlusion - i.e. at concave vertices. Each segment is matched against known model objects by calculating a matching measure, which is defined as the minimum euclidean distance between the shape functions. An O(mm(n+m) algorithm for computing the measure is presentd, where n and m are the number of veritces for a model and an unknown object, respectively. Match results from aprtial segments are combined based on mutual compatibility, then are verified using distance transformation and translation vector to produce the final recognition. The proposed algorithm is invariant under translation and rotation of objects, which has been shown by experimental results.

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Ear Recognition by Major Axis and Complex Vector Manipulation

  • Su, Ching-Liang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.3
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    • pp.1650-1669
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    • 2017
  • In this study, each pixel in an ear is used as a centroid to generate a cake. Subsequently the major axis length of this cake is computed and obtained. This obtained major axis length serves as a feature to recognize an ear. Later, the ear hole is used as a centroid and a 16-circle template is generated to extract the major axis lengths of the ear. The 16-circle template extracted signals are used to recognize an ear. In the next step, a ring-to-line mapping technique is used to map these major axis lengths to several straight-line signals. Next, the complex plane vector computing technique is used to determine the similarity of these major axis lengths, whereby a solution to the image-rotating problem is achieved. The aforementioned extracted signals are also compared to the ones that are extracted from its neighboring pixels, whereby solving the image-shifting problem. The algorithm developed in this study can precisely identify an ear image by solving the image rotation and image shifting problems.

Development of Morphological Pattern Recognition System - Morphological Shape Decomposition using Shape Function (형태론적 패턴인식 시스템의 개발 - 형상함수를 이용한 형태론적 형상분해)

  • Jong Ho Choi
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.8
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    • pp.1127-1136
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    • 1995
  • In this paper, a morphological shape decomposition method is proposed for the purpose of pattern recognition and image compression. In the method, a structuring element that geometrical characteristics is more similar to the shape function is preselected. The shape is decomposed into the primitive elements corresponding to the structuring element. A gray scale image also is transformed into 8 bit plane images for the hierarchical reconstruction required in image communication systems. The shape in each bitplane is decomposed to the proposed method. Through the experiment. it is proved that the description error is reduced and the coding efficiency is improved.

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Korean Character Recognition with Tree Structure Using Representative Images (대표영상을 이용한 나무구조의 한글문자 인식)

  • 김정우;정수길;조웅호;김성용;김수중
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.4
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    • pp.18-29
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    • 1994
  • For the efficient recognition of Korean Alphabets, we proposed the tree structure algorithm which was based on K-tuple NRF-SDF using representative images as training images. Representative images consisted of ECP-SDF images of several consonants or vowels. To reduce the effect of sidelobe in the output correlation plane, we used the representative images as training images and obtained the elements of a vector inner product matrix using the peak value of AMPOF correlation of training images with one another. The proposed algorithm consisted of three main-step containing several substeps. In filter synthesis of each step, representative images were used as training images in the first and the second main-step and each consonant or vowel was used as training images in the third main-step. The performance of this algorithm is demonstrated by computer simulation and optical experiment.

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Recognition of 3D hand gestures using partially tuned composite hidden Markov models

  • Kim, In Cheol
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.236-240
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    • 2004
  • Stroke-based composite HMMs with articulation states are proposed to deal with 3D spatio-temporal trajectory gestures. The direct use of 3D data provides more naturalness in generating gestures, thereby avoiding some of the constraints usually imposed to prevent performance degradation when trajectory data are projected into a specific 2D plane. Also, the decomposition of gestures into more primitive strokes is quite attractive, since reversely concatenating stroke-based HMMs makes it possible to construct a new set of gesture HMMs without retraining their parameters. Any deterioration in performance arising from decomposition can be remedied by a partial tuning process for such composite HMMs.