• Title/Summary/Keyword: Intersection Recognition Algorithm

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Machining Feature Recognition with Intersection Geometry between Design Primitives (설계 프리미티브 간의 교차형상을 통한 가공 피쳐 인식)

  • 정채봉;김재정
    • Korean Journal of Computational Design and Engineering
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    • v.4 no.1
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    • pp.43-51
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    • 1999
  • Producing the relevant information (features) from the CAD models of CAM, called feature recognition or extraction, is the essential stage for the integration of CAD and CAM. Most feature recognition methods, however, have problems in the recognition of intersecting features because they do not handle the intersection geometry properly. In this paper, we propose a machining feature recognition algorithm, which has a solid model consisting of orthogonal primitives as input. The algorithm calculates candidate features and constitutes the Intersection Geometry Matrix which is necessary to represent the spatial relation of candidate features. Finally, it recognizes machining features from the proposed candidate features dividing and growing systems using half space and Boolean operation. The algorithm has the following characteristics: Though the geometry of part is complex due to the intersections of design primitives, it can recognize the necessary machining features. In addition, it creates the Maximal Feature Volumes independent of the machining sequences at the feature recognition stage so that it can easily accommodate the change of decision criteria of machining orders.

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Computational Complexity Reduction of Speech Recognizers Based on the Modified Bucket Box Intersection Algorithm (변형된 BBI 알고리즘에 기반한 음성 인식기의 계산량 감축)

  • Kim, Keun-Yong;Kim, Dong-Hwa
    • MALSORI
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    • no.60
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    • pp.109-123
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    • 2006
  • Since computing the log-likelihood of Gaussian mixture density is a major computational burden for the speech recognizer based on the continuous HMM, several techniques have been proposed to reduce the number of mixtures to be used for recognition. In this paper, we propose a modified Bucket Box Intersection (BBI) algorithm, in which two relative thresholds are employed: one is the relative threshold in the conventional BBI algorithm and the other is used to reduce the number of the Gaussian boxes which are intersected by the hyperplanes at the boxes' edges. The experimental results show that the proposed algorithm reduces the number of Gaussian mixtures by 12.92% during the recognition phase with negligible performance degradation compared to the conventional BBI algorithm.

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Development of Color Recognition Algorithm for Traffic Lights using Deep Learning Data (딥러닝 데이터 활용한 신호등 색 인식 알고리즘 개발)

  • Baek, Seoha;Kim, Jongho;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.14 no.2
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    • pp.45-50
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    • 2022
  • The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.

An Efficient Broadcast Scheme for Disseminating Emergency Message in Urban Vehicular Ad-Hoc Networks (도심의 차량 네트워크에서 긴급 메시지 전파를 위한 효율적인 브로드캐스트 기법)

  • Lee, Kyu-Chang;Han, Ki-Jun;Cho, Keu-Chul;Baek, Young-Mi;Kim, Jun-Hyung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.7
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    • pp.605-611
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    • 2013
  • If an accident vehicle propagates emergency messages to other vehicles close to it, the other drivers may realize and avoid the accident spot. In this letter, we propose a broadcast scheme to propagate emergency messages fast in urban VANETs (Vehicular Ad-Hoc Networks) with the help of GPS (Global Position System). In our scheme, a transmitting vehicle chooses the farthest node as the next relay vehicle to propagate emergency messages. And, we suggest an algorithm for intersection recognition and SCF (Store-Carry-Forward) task by taking advantage of periodic hello packets to reduce the propagation time and enhance the delivery ratio.

Improvement of Three Mixture Fragrance Recognition using Fuzzy Similarity based Self-Organized Network Inspired by Immune Algorithm

  • Widyanto, M.R.;Kusumoputro, B.;Nobuhara, H.;Kawamoto, K.;Yoshida, S.;Hirota, K.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.419-422
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    • 2003
  • To improve the recognition accuracy of a developed artificial odor discrimination system for three mixture fragrance recognition, Fuzzy Similarity based Self-Organized Network inspired by Immune Algorithm (F-SONIA) is proposed. Minimum, average, and maximum values of fragrance data acquisitions are used to form triangular fuzzy numbers. Then the fuzzy similarity treasure is used to define the relationship between fragrance inputs and connection strengths of hidden units. The fuzzy similarity is defined as the maximum value of the intersection region between triangular fuzzy set of input vectors and the connection strengths of hidden units. In experiments, performances of the proposed method is compared with the conventional Self-Organized Network inspired by Immune Algorithm (SONIA), and the Fuzzy Learning Vector Quantization (FLVQ). Experiments show that F-SONIA improves recognition accuracy of SONIA by 3-9%. Comparing to the previously developed artificial odor discrimination system that used FLVQ as pattern classifier, the recognition accuracy is increased by 14-25%.

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An Enhanced Fuzzy ART Algorithm for The Effective Identifier Recognition From Shipping Container Image (효과적인 운송 컨테이너 영상의 식별자 인식을 위한 개선된 퍼지 ART 알고리즘)

  • 김광백
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.5C
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    • pp.486-492
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    • 2003
  • The vigilance threshold of conventional fuzzy ART algorithm decide whether to permit the mismatch between any input pattern and stored pattern. If the vigilance threshold was large, despite of little difference among input and stored patterns, the input pattern may be classified to new category. On the other hand, if the vigilance threshold was small, the similarity between two patterns may be accepted in spite of lots of difference and the input pattern are classified to category of the stored pattern. Therefore, the vigilance threshold for the image recognition must be experientially set for the good result. Moreover, it may occur in the fuzzy ART algorithm that the information of stored patterns is lost in the weight-adjusting process and the rate of pattern recognition is dropped. In this paper, I proposed the enhanced fuzzy ART algorithm that supports the dynamical setting of the vigilance threshold using the generalized intersection operator of fuzzy logic and the weight value being adaptively set in proportional to the current weight change and the previous weight by reflecting the frequency of the selection of winner node. For the performance evaluation of the proposed method, we applied to the recognition of container identifiers from shipping container images. The experiment showed that the proposed method produced fewer clusters than conventional ART2 and fuzzy ART algorithm. and had tile higher recognition rate.

Reconstruction of Overlapping Character in Thai Printed Documents

  • Nucharee Pemchaiswa;Wichian Premchaiswadi;Voravit Premratanachai;Seinosuke Narita
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.31-34
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    • 2000
  • This paper proposes a reconstruction scheme for overlapping characters in Thai printed document. Overlapping characters are characters that overlap with surrounding characters. The problem of overlapping characters is still an unsolved problem In commercially available software of Thai character recognition systems. The algorithm of reconstruction scheme is based on structural analysis of overlapping Thai printed characters. It consists of 2 steps: overlapping point determination and reconstruction of segmented characters. The overlapping point is defined as the intersection point between characters and can be determined by using templates. Then, an overlapping character is separated into segments at the intersection point. The structure of each segment may be an incomplete character and is not identical to the original one. Therefore, the reconstruction process is employed to add the incomplete part of these segments. The proposed scheme has been implemented and tested with 70 patterns of conventionally found in overlapping printed Thai characters with different typefaces and type sizes. The experimental results show that the proposed scheme can segment and reconstruct overlapping characters correctly. The proposed scheme can improve the recognition rate of commercially available software, ThaiOCR1.5 and ArnThai1.0, more than 60 percents

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Multiple Camera-Based Correspondence of Ground Foot for Human Motion Tracking (사람의 움직임 추적을 위한 다중 카메라 기반의 지면 위 발의 대응)

  • Seo, Dong-Wook;Chae, Hyun-Uk;Jo, Kang-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.8
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    • pp.848-855
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    • 2008
  • In this paper, we describe correspondence among multiple images taken by multiple cameras. The correspondence among multiple views is an interesting problem which often appears in the application like visual surveillance or gesture recognition system. We use the principal axis and the ground plane homography to estimate foot of human. The principal axis belongs to the subtracted silhouette-based region of human using subtraction of the predetermined multiple background models with current image which includes moving person. For the calculation of the ground plane homography, we use landmarks on the ground plane in 3D space. Thus the ground plane homography means the relation of two common points in different views. In the normal human being, the foot of human has an exactly same position in the 3D space and we represent it to the intersection in this paper. The intersection occurs when the principal axis in an image crosses to the transformed ground plane from other image. However the positions of the intersection are different depend on camera views. Therefore we construct the correspondence that means the relationship between the intersection in current image and the transformed intersection from other image by homography. Those correspondences should confirm within a short distance measuring in the top viewed plane. Thus, we track a person by these corresponding points on the ground plane. Experimental result shows the accuracy of the proposed algorithm has almost 90% of detecting person for tracking based on correspondence of intersections.

Localization of Mobile Robot Using Color Landmark mounted on Ceiling (천장 부착 컬러 표식을 이용한 이동로봇의 자기위치추정)

  • Oh, Jong-Kyu;Lee, Chan-Ho
    • Proceedings of the KIEE Conference
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    • 2001.11c
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    • pp.91-94
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    • 2001
  • In this paper, we proposed localization method of mobile robot using color landmark mounted on ceiling. This work is composed 2 parts : landmark recognition part which finds the position of multiple landmarks in image and identifies them and absolute position estimation part which estimates the location and orientation of mobile robot in indoor environment. In landmark recognition part, mobile robot detects artificial color landmarks using simple histogram intersection method in rg color space which is insensitive to the change of illumination. Then absolute position estimation part calculates relative position of the mobile robot to the detected landmarks. For the verification of proposed algorithm, ceiling-orientated camera was installed on a mobile robot and performance of localization was examined by designed artificial color landmarks. As the result of test, mobile robot could achieve the reliable landmark detection and accurately estimate the position of mobile robot in indoor environment.

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A Study on Image Recognition using Enhanced ART1 Algorithm (개선된 ART1 알고리즘을 이용한 이미지 인식에 관한 연구)

  • 천두억;윤성호;김광백
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.3
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    • pp.17-22
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    • 1998
  • As time goes on, that becomes an issue still more for truth from error of a seal in electronic settlement , or in important document in the field of image recognition. But on the other hand image treatment method of a seal have has the weakness until now. It makes indistinct distinction of part that light and darkness is changed sharply as the edge of things. So it has difficult that edge detection is extracted. In this paper, I investigated the pixel in a specific area by using enhanced smothing method and searched a value of frquent occurrence. The value of pixel is substituted and edge detection is extracted. After then it could be classified rightly according as viligence test is dynamically changed. I applied conventional of Yager's generated intersection operator among fuzzy logic operator in ART1 learning Algorithm. Application of suggested ART1 learning algorithm, it results in improved image recognition rate than a case of using the conventional ART1 algorithm

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