• 제목/요약/키워드: Boundary detection

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Detection of Cavities by Inverse Heat Conduction Boundary Element Method Using Minimal Energy Technique (최소 에너지기법을 이용한 역 열전도 경계요소법의 공동 탐지)

  • Choi, C.Y.
    • Journal of the Korean Society for Nondestructive Testing
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    • v.17 no.4
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    • pp.237-247
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    • 1997
  • A geometrical inverse heat conduction problem is solved for the infrared scanning cavity detection by the boundary element method using minimal energy technique. By minimizing the kinetic energy of temperature field, boundary element equations are converted to the quadratic programming problem. A hypothetical inner boundary is defined such that the actual cavity is located interior to the domain. Temperatures at hypothetical inner boundary are determined to meet the constraints of mea- surement error of surface temperature obtained by infrared scanning, and then boundary element analysis is peformed for the position of an unknown boundary (cavity). Cavity detection algorithm is provided, and the effects of minimal energy technique on the inverse solution method are investigated by means of numerical analysis.

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An Efficient Contact Detection Algorithm for Contact Problems with the Boundary Element Method (경계요소법을 이용한 접촉해석의 효율적인 접촉면 검출기법)

  • Kim, Moon-Kyum;Yun, Ik-Jung
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.22 no.5
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    • pp.439-444
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    • 2009
  • This paper presents an efficient contact detection algorithm for the plane elastostatic contact problem of the boundary element method(BEM). The data structures of the boundary element method are dissected to develop an efficient contact detection algorithm. This algorithm is consists of three parts as global searching, local searching and contact relation setting to reflect the corner node problem. Contact master and slave type elements are used in global searching step and quad-tree is selected as the spatial decomposition method in local searching step. To set up contact relation equations, global contact searching is conducted at node level and local searching is performed at element level. To verify the efficiency of the proposed contact detection algorithm of BEM, numerical example is presented.

Correction of Signboard Distortion by Vertical Stroke Estimation

  • Lim, Jun Sik;Na, In Seop;Kim, Soo Hyung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.9
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    • pp.2312-2325
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    • 2013
  • In this paper, we propose a preprocessing method that it is to correct the distortion of text area in Korean signboard images as a preprocessing step to improve character recognition. Distorted perspective in recognizing of Korean signboard text may cause of the low recognition rate. The proposed method consists of four main steps and eight sub-steps: main step consists of potential vertical components detection, vertical components detection, text-boundary estimation and distortion correction. First, potential vertical line components detection consists of four steps, including edge detection for each connected component, pixel distance normalization in the edge, dominant-point detection in the edge and removal of horizontal components. Second, vertical line components detection is composed of removal of diagonal components and extraction of vertical line components. Third, the outline estimation step is composed of the left and right boundary line detection. Finally, distortion of the text image is corrected by bilinear transformation based on the estimated outline. We compared the changes in recognition rates of OCR before and after applying the proposed algorithm. The recognition rate of the distortion corrected signboard images is 29.63% and 21.9% higher at the character and the text unit than those of the original images.

Tillage boundary detection based on RGB imagery classification for an autonomous tractor

  • Kim, Gookhwan;Seo, Dasom;Kim, Kyoung-Chul;Hong, Youngki;Lee, Meonghun;Lee, Siyoung;Kim, Hyunjong;Ryu, Hee-Seok;Kim, Yong-Joo;Chung, Sun-Ok;Lee, Dae-Hyun
    • Korean Journal of Agricultural Science
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    • v.47 no.2
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    • pp.205-217
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    • 2020
  • In this study, a deep learning-based tillage boundary detection method for autonomous tillage by a tractor was developed, which consisted of image cropping, object classification, area segmentation, and boundary detection methods. Full HD (1920 × 1080) images were obtained using a RGB camera installed on the hood of a tractor and were cropped to 112 × 112 size images to generate a dataset for training the classification model. The classification model was constructed based on convolutional neural networks, and the path boundary was detected using a probability map, which was generated by the integration of softmax outputs. The results show that the F1-score of the classification was approximately 0.91, and it had a similar performance as the deep learning-based classification task in the agriculture field. The path boundary was determined with edge detection and the Hough transform, and it was compared to the actual path boundary. The average lateral error was approximately 11.4 cm, and the average angle error was approximately 8.9°. The proposed technique can perform as well as other approaches; however, it only needs low cost memory to execute the process unlike other deep learning-based approaches. It is possible that an autonomous farm robot can be easily developed with this proposed technique using a simple hardware configuration.

Robust Speech Detection Based on Useful Bands for Continuous Digit Speech over Telephone Networks

  • Ji, Mi-Kyongi;Suh, Young-Joo;Kim, Hoi-Rin;Kim, Sang-Hun
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.3E
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    • pp.113-123
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    • 2003
  • One of the most important problems in speech recognition is to detect the presence of speech in adverse environments. In other words, the accurate detection of speech boundary is critical to the performance of speech recognition. Furthermore the speech detection problem becomes severer when recognition systems are used over the telephone network, especially wireless network and noisy environment. Therefore this paper describes various speech detection algorithms for continuous digit recognition system used over wire/wireless telephone networks and we propose a algorithm in order to improve the robustness of speech detection using useful band selection under noisy telephone networks. In this paper, we compare some speech detection algorithms with the proposed one, and present experimental results done with various SNRs. The results show that the new algorithm outperforms the other speech detection methods.

New Shot Boundary Detection Using Local $X^2$-Histogram and Normalization (지역적 $X^2$-히스토그램과 정규화를 이용한 새로운 샷 경계 검출)

  • Shin, Seong-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.103-109
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    • 2007
  • In this paper, we detect shot boundaries using $X^2$-histogram comparison method which have enough spatial information that is more robust to the camera or object motion and produce more precise results. Also, we present normalization method to change Log-Formula and constant that is used for contrast enhancement of image in image processing and apply in difference value. And, present shot boundary detection algorithm to detect shot boundary based on general shot and abrupt shot's characteristic.

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Topological Boundary Detection in Wireless Sensor Networks

  • Dinh, Thanh Le
    • Journal of Information Processing Systems
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    • v.5 no.3
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    • pp.145-150
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    • 2009
  • The awareness of boundaries in wireless sensor networks has many benefits. The identification of boundaries is especially challenging since typical wireless sensor networks consist of low-capability nodes that are unaware of their geographic location. In this paper, we propose a simple, efficient algorithm to detect nodes that are near the boundary of the sensor field as well as near the boundaries of holes. Our algorithm relies purely on the connectivity information of the underlying communication graph and does not require any information on the location of nodes. We introduce the 2-neighbor graph concept, and then make use of it to identify nodes near boundaries. The results of our experiment show that our algorithm carries out the task of topological boundary detection correctly and efficiently.

Detection of the Optic Disk Boundary in Retinal Images Using Inward and Outward Curve Evolution (양방향 곡선 전개 방식을 이용한 망막영상에서의 시신경 원판 경계 검출)

  • Lee Sang-Kwan;Kim Seong-Kon
    • The Journal of the Korea Contents Association
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    • v.5 no.6
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    • pp.138-145
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    • 2005
  • This paper describes a technique for detecting the boundary of the optic disk in digital image of the retina using inward and outward curve evolution. This paper offers medical information about glaucoma progresses. For accurate boundary detection, image inpainting based on texture synthesis removes blood vessels crossing the optic disk. For removing noises and preserving boundary of optic disk in image inpainting process, the anisotropic diffusion filtering is necessary. After pre-processing, the optic disk boundary is determined using inward and outward curve evolution. The experimental results show that the algorithm is effective for detection of optic disk boundary.

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Modified Canny Edge Detection Algorithm for Detecting Subway Platform Screen Door Invasion (지하철 플랫폼 스크린 도어 침범 인식을 위한 변형된 캐니에지 검출 알고리듬)

  • Lee, Ha-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.4
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    • pp.663-670
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    • 2019
  • The modified Canny edge detection algorithm that can detect the boundary between screen door and platform in the subway is proposed in this paper. Generally, in the subway, the boundary line between the platform and the screen door is darker than the surrounding area. Therefore, an edge image is using the modified bottom-hat transform by considering its characteristics. Double thresholded images with strong edge and weak edge through double thresholding are obtained. An algorithm that detects the boundary invasion between the platform and the screen door is proposed by calculating the length by applying the Hough transform to the double thresholded image and comparing the boundary line length between when there is an object such as a person and when there is no object. In this paper, the results of the proposed modified Canny edge detection algorithm using two different input images according to camera height position are shown by computer simulation.

EBCO - Efficient Boundary Detection and Tracking Continuous Objects in WSNs

  • Chauhdary, Sajjad Hussain;Lee, Jeongjoon;Shah, Sayed Chhattan;Park, Myong-Soon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.11
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    • pp.2901-2919
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    • 2012
  • Recent research in MEMS (Micro-Electro-Mechanical Systems) and wireless communication has enabled tracking of continuous objects, including fires, nuclear explosions and bio-chemical material diffusions. This paper proposes an energy-efficient scheme that detects and tracks different dynamic shapes of a continuous object (i.e., the inner and outer boundaries of a continuous object). EBCO (Efficient Boundary detection and tracking of Continuous Objects in WSNs) exploits the sensing capabilities of sensor nodes by automatically adjusting the sensing range to be either a boundary sensor node or not, instead of communicating to its neighboring sensor nodes because radio communication consumes more energy than adjusting the sensing range. The proposed scheme not only increases the tracking accuracy by choosing the bordering boundary sensor nodes on the phenomenon edge, but it also minimizes the power consumption by having little communication among sensor nodes. The simulation result shows that our proposed scheme minimizes the energy consumption and achieves more precise tracking results than existing approaches.