• 제목/요약/키워드: Automatic search algorithm

검색결과 126건 처리시간 0.021초

광부품 정렬 자동화를 위한 최적 탐색 알고리즘 연구 (Sturdy on the Optimal Search Algorithm for the Automatic Alignment of Fiber Optic Components)

  • 지상우;임경화;강희석;조영준
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2002년도 추계학술대회 논문집
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    • pp.451-454
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    • 2002
  • The fiber optic communication technology is considered as a key solution for the future communication. However the assembly of the fiber optic components highly depends on manual or semi-automated alignment process. And the light search algorithm is recognized an important factor to reduce the manufacturing process time. Therefore this paper investigates optimal search algorithm for the automatic alignment of fiber optic components. The experiments show the effectiveness of Hill Climbing Search, Adaptive Hill Climbing Search and Steepest Search algorithms, in a view of process time.

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Development of a Semi-automatic Search Program for Crown Delineation Based on Watershed and Valley Following Algorithms

  • Sim, Woodam;Park, Jeongmook;Lee, Jungsoo
    • Journal of Forest and Environmental Science
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    • 제34권2호
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    • pp.142-144
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    • 2018
  • This paper discusses the development of semi-automatic search program for crown delineation in stand level. The crown of an individual tree was delineated by applying the Watershed (WS) and Valley Following (VF) algorithms. Unmanned Aerial Vehicle (UAV) images were used in the semi-automatic search program to delineate the crown area. The overall accuracy and Khat were used in accuracy assessment. WS algorithm's model showed the overall accuracy and Khat index of 0.80 and 0.59, respectively, in Plot 1. However, the overall accuracy and Khat of VF algorithm's model were 0.78 and 0.51, respectively, in Plot 2.

ACA: Automatic search strategy for radioactive source

  • Jianwen Huo;Xulin Hu;Junling Wang;Li Hu
    • Nuclear Engineering and Technology
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    • 제55권8호
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    • pp.3030-3038
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    • 2023
  • Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.

TFT-LCD 자동 수선시스템에서 결함이 있는 셀을 자동으로 추출하는 방법 (Defect Cell Extraction for TFT-LCD Auto-Repair System)

  • 조재수;하광성;이진욱;김동현;전재웅
    • 제어로봇시스템학회논문지
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    • 제14권5호
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    • pp.432-437
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    • 2008
  • This paper proposes a defect cell extraction algorithm for TFT-LCD auto-repair system. Auto defect search algorithm and automatic defect cell extraction method are very important for TFT-LCD auto repair system. In the previous literature[1], we proposed an automatic visual inspection algorithm of TFT-LCD. Based on the inspected information(defect size and defect axis, if defect exists) by the automatic search algorithm, defect cells should be extracted from the input image for the auto repair system. For automatic extraction of defect cells, we used a novel block matching algorithm and a simple filtering process in order to find a given reference point in the LCD cell. The proposed defect cell extraction algorithm can be used in all kinds of TFT-LCD devices by changing a stored template which includes a given reference point. Various experimental results show the effectiveness of the proposed method.

칼만 필터와 가변적 탐색 윈도우 기법을 적용한 강인한 이동 물체 추적 알고리즘 (Robust Tracking Algorithm for Moving Object using Kalman Filter and Variable Search Window Technique)

  • 김영군;현병용;조영완;서기성
    • 제어로봇시스템학회논문지
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    • 제18권7호
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    • pp.673-679
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    • 2012
  • This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

Maximum Likelihood Estimation for the Laplacian Autoregressive Time Series Model

  • Son, Young-Sook;Cho, Sin-Sup
    • Journal of the Korean Statistical Society
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    • 제25권3호
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    • pp.359-368
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    • 1996
  • The maximum likelihood estimation is discussed for the NLAR model with Laplacian marginals. Since the explicit form of the estimates cannot be obtained due to the complicated nature of the likelihood function we utilize the automatic computer optimization subroutine using a direct search complex algorithm. The conditional least square estimates are used as initial estimates in maximum likelihood procedures. The results of a simulation study for the maximum likelihood estimates of the NLAR(1) and the NLAR(2) models are presented.

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Sorting Instagram Hashtags all the Way throw Mass Tagging using HITS Algorithm

  • D.Vishnu Vardhan;Dr.CH.Aparna
    • International Journal of Computer Science & Network Security
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    • 제23권11호
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    • pp.93-98
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    • 2023
  • Instagram is one of the fastest-growing online photo social web services where users share their life images and videos with other users. Image tagging is an essential step for developing Automatic Image Annotation (AIA) methods that are based on the learning by example paradigm. Hashtags can be used on just about any social media platform, but they're most popular on Twitter and Instagram. Using hashtags is essentially a way to group together conversations or content around a certain topic, making it easy for people to find content that interests them. Practically on average, 20% of the Instagram hashtags are related to the actual visual content of the image they accompany, i.e., they are descriptive hashtags, while there are many irrelevant hashtags, i.e., stophashtags, that are used across totally different images just for gathering clicks and for search ability enhancement. Hence in this work, Sorting instagram hashtags all the way through mass tagging using HITS (Hyperlink-Induced Topic Search) algorithm is presented. The hashtags can sorted to several groups according to Jensen-Shannon divergence between any two hashtags. This approach provides an effective and consistent way for finding pairs of Instagram images and hashtags, which lead to representative and noise-free training sets for content-based image retrieval. The HITS algorithm is first used to rank the annotators in terms of their effectiveness in the crowd tagging task and then to identify the right hashtags per image.

Automatic Registration of Two Parts using Robot with Multiple 3D Sensor Systems

  • Ha, Jong-Eun
    • Journal of Electrical Engineering and Technology
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    • 제10권4호
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    • pp.1830-1835
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    • 2015
  • In this paper, we propose an algorithm for the automatic registration of two rigid parts using multiple 3D sensor systems on a robot. Four sets of structured laser stripe system consisted of a camera and a visible laser stripe is used for the acquisition of 3D information. Detailed procedures including extrinsic calibration among four 3D sensor systems and hand/eye calibration of 3D sensing system on robot arm are presented. We find a best pose using search-based pose estimation algorithm where cost function is proposed by reflecting geometric constraints between sensor systems and target objects. A pose with minimum gap and height difference is found by greedy search. Experimental result using demo system shows the robustness and feasibility of the proposed algorithm.

HMM 및 보정 알고리즘을 이용한 자동 음성 분할 시스템 (An Automatic Segmentation System Based on HMM and Correction Algorithm)

  • 김무중;권철홍
    • 음성과학
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    • 제9권4호
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    • pp.265-274
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    • 2002
  • In this paper we propose an automatic segmentation system that outputs the time alignment information of phoneme boundary using Viterbi search with HMM (Hidden Markov Model) and corrects these results by an UVS (unvoiced/voiced/silence) classification algorithm. We selecte a set of 39 monophones and a set of 647 extended phones for HMM models. For the UVS classification we use the feature parameters such as ZCR (Zero Crossing Rate), log energy, spectral distribution. The result of forced alignment using the extended phone set is 11% better than that of the monophone set. The UVS classification algorithm shows high performance to correct the segmentation results.

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모양공간 모델을 이용한 영상분할 알고리즘 (An Image Segmentation Algorithm using the Shape Space Model)

  • 김대희;안충현;호요성
    • 대한전자공학회논문지SP
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    • 제41권2호
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    • pp.41-50
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    • 2004
  • MPEG-4 표준에서는 객체 단위의 부호화를 수행하기 위해 자연영상으로부터 비디오 객체를 분리하는 영상분할(segmentation) 기술이 필요하다. 영상분할 방법은 크게 자동 영상분할(automatic segmentation)과 반자동 영상분할(semi-automatic segmentation)의 두 부류로 나눌 수 있다. 지금까지 개발된 대부분의 자동 영상분할 방법은 비디오 객체의 명확한 수학적인 모델을 제시하기 곤란하며 한 화면에서 개별 객체를 추출하기 어렵기 때문에 그 성능에 한계가 있다. 본 논문에서는 이러한 문제점을 극복하기 위해 active contour 알고리즘을 이용한 반자동 영상분할 알고리즘을 제안한다. 초기 곡선으로부터 변화 가능한 모든 곡선의 집합을 모양공간으로 정의하고 그 공간을 선형공간이라고 가정하면, 모양공간(shape space)은 모양 행렬에 의해 행(column) 공간과 남은 빈(left null) 공간으로 나뉘어진다. 본 논문에서 제안하는 알고리즘은 행공간의 모양공간 벡터를 이용하여 초기 곡선으로부터 영상의 특징점까지의 변화를 기술하고 동적 그래프 검색 알고리즘을 이용하여 객체의 세밀한 부분을 묘사한다. 모양 행렬과 객체의 윤곽을 추정하기 위한 SUSAN 연산자의 사용으로 제안한 알고리즘은 저수준 영상처리로부터 생성되는 불필요한 특징점을 무시할 수 있다. 또한, 모양 행렬의 사용으로 생긴 제약은 동적 그래프 검색 알고리즘으로 보상한다.