• Title/Summary/Keyword: thinning algorithm

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A Modified WPTA Thinning Algorithm (수정된 WPTA 세선화 알고리즘)

  • Won, Nam-Sik;Nam, In-Gil;Jeon, Il-Su
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.10
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    • pp.2823-2829
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    • 1999
  • This paper is a study on the improvement of WPTA algorithm available for the recognition of various characters. WPTA algorithm can extract the skeleton of a character almost similar to the original pattern by using the connection value representing connectivity of each pixel. In this paper we show that the skeleton disappearance phenomena existing in WPTA and propose modified algorithm which can eliminate this phenomena.

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A Study on the Preprocessing Method Using Construction of Watershed for Character Image segmentation

  • Nam Sang Yep;Choi Young Kyoo;Kwon Yun Jung;Lee Sung Chang
    • Proceedings of the IEEK Conference
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    • 2004.08c
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    • pp.814-818
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    • 2004
  • Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

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Automated radiation field edge detection in portal image using optimal threshold value (최적 문턱치 설정을 이용한 포탈영상에서의 자동 에지탐지 기법에 관한 연구)

  • 허수진
    • Journal of Biomedical Engineering Research
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    • v.16 no.3
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    • pp.337-344
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    • 1995
  • Because of the high energy of the treatment beam, contrast of portal films is very poor. Many image processing techniques have been applied to the portal images but a significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it may be remedied by separating the treatment field from the background prior to enhancement and uslng only the pixels within the field boundary in the enhancement procedure. A new edge extraction algorithm for accurate extraction of the radiation field boundary from portal Images has been developed for contrast enhancement of portal images. In this paper, portal image segmentation algorithm based on Sobel filtration, labelling processes and morphological thinning has been presented. This algorithm could automatically search the optimal threshold value which is sensitive to the variation of the type and quality of portal images.

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A Method for Finger Vein Recognition using a New Matching Algorithm (새로운 정합 알고리즘을 이용한 손가락 정맥 인식 방법)

  • Kim, Hee-Sung;Cho, Jun-Hee
    • Journal of KIISE:Software and Applications
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    • v.37 no.11
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    • pp.859-865
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    • 2010
  • In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.

Seam Carving based Occlusion Region Compensation Algorithm (심카빙 기반 가려짐 영역 보상 기법)

  • An, Jae-Woo;Yoo, Ji-Sang
    • Journal of Broadcast Engineering
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    • v.16 no.4
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    • pp.573-583
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    • 2011
  • In this paper, we propose an occlusion compensation algorithm which is used for virtual view generation. In general, since occlusion region is recovered from neighboring pixels by taking the mean value or median value of neighbor pixels, the visual characteristics of a given image are not considered and consequently the accuracy of the compensated occlusion regions is not guaranteed. To solve these problem, we propose an algorithm that considers primary visual characteristics of a given image to compensate the occluded regions by using seam carving algorithm. In the proposed algorithm, we first use Sobel mask to obtain the edge map of a given image and then make it binary digit 0 or 1 and finally thinning process follows. Then, the energy patterns of original and thinned edge map obtained by the modified seam carving method are used to compensate the occlusion regions. Through experiments with many test images, we verify that the proposed algorithm performed better than conventional algorithms.

Analysis of Optimal Thinning Prescriptions for a Cryptomeria japonica Stand Using Dynamic Programming (동적계획법 적용에 의한 삼나무 임분의 간벌시업체계 분석)

  • Han, Hee;Kwon, Kibeom;Chung, Hyejean;Seol, Ara;Chung, Joosang
    • Journal of Korean Society of Forest Science
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    • v.104 no.4
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    • pp.649-656
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    • 2015
  • The objective of this study was to analyze the optimal thinning regimes for timber or carbon managements in Cryptomeria japonica stands of Hannam Experimental Forest, Korea Forest Research Institute. In solving the problem, PATH algorithm, developed by Paderes and Brodie, was used as the decision-making tool and the individual-tree/distance-free stand growth simulator for the species, developed by Kwon et al., was used to predict the stand growth associated with density control by thinning regimes and mortality. The results of this study indicate that the timber management for maximum net present value (NPV) needs less number of but higher intensity thinnings than the carbon management for maximum carbon absorption does. In case of carbon management, the amount of carbon absorption is bigger than that of timber management by about 6% but NPV is reduced by about 3.2%. On the other hand, intensive forest managements with thinning regimes promotes net income and carbon absorption by about 60% compared with those of the do-nothing option.

Improved Exploration Algorithm Using Reliability Index of Thinning Based Topological Nodes

  • Kwon, Tae-Bum;Song, Jae-Bok;Lee, Soo-Yong
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.250-255
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    • 2005
  • For navigation of a service robot, mapping and localization are very important. To estimate the robot pose, the map of the environment is required and it can be built by exploration or SLAM. Exploration is the fundamental task of guiding a robot autonomously during mapping such that it covers the entire environment with its sensors. In this paper, an efficient exploration scheme based on the position probability of the end nodes of a topological map is proposed. In this scheme, a topological map is constructed in real time using the thinning-based approach. The robot then updates the position probability of each end node maintaining its position at the current location based on the Bayesian update rule using the range data. From this probability, the robot can determine whether or not it needs to visit the specific end node to examine the environment around this node. Various experiments show that the proposed exploration scheme can perform exploration more efficiently than other schemes in that, in most cases, exploration for the entire environment can be completed without directly visiting everywhere in the environment.

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Collapse moment estimation for wall-thinned pipe bends and elbows using deep fuzzy neural networks

  • Yun, So Hun;Koo, Young Do;Na, Man Gyun
    • Nuclear Engineering and Technology
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    • v.52 no.11
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    • pp.2678-2685
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    • 2020
  • The pipe bends and elbows in nuclear power plants (NPPs) are vulnerable to degradation mechanisms and can cause wall-thinning defects. As it is difficult to detect both the defects generated inside the wall-thinned pipes and the preliminary signs, the wall-thinning defects should be accurately estimated to maintain the integrity of NPPs. This paper proposes a deep fuzzy neural network (DFNN) method and estimates the collapse moment of wall-thinned pipe bends and elbows. The proposed model has a simplified structure in which the fuzzy neural network module is repeatedly connected, and it is optimized using the least squares method and genetic algorithm. Numerical data obtained through simulations on the pipe bends and elbows with extrados, intrados, and crown defects were applied to the DFNN model to estimate the collapse moment. The acquired databases were divided into training, optimization, and test datasets and used to train and verify the estimation model. Consequently, the relative root mean square (RMS) errors of the estimated collapse moment at all the defect locations were within 0.25% for the test data. Such a low RMS error indicates that the DFNN model is accurate in estimating the collapse moment for wall-thinned pipe bends and elbows.

Automatic Matching of Multi-Sensor Images Using Edge Detection Based on Thinning Algorithm (세선화 알고리즘 기반의 에지검출을 이용한 멀티센서 영상의 자동매칭)

  • Shin, Sung-Woong;Kim, Jun-Chul;Oh, Kum-Hui;Lee, Young-Ran
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.4
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    • pp.407-414
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    • 2008
  • This study introduces an automatic image matching algorithm that can be applied for the scale different image pairs consisting of the satellite pushbroom images and the aerial frame images. The proposed method is based on several image processing techniques such as pre-processing, filtering, edge thinning, interest point extraction, and key-descriptor matching, in order to enhance the matching accuracy and the processing speed. The proposed method utilizes various characteristics, such as the different geometry of image acquisition and the different radiometric characteristics, of the multi-sensor images. In addition, the suggested method uses the sensor model to minimize search area and eliminate false-matching points automatically.

선형 신경 회로망을 이용한 영상 Thinning 구현

  • 박병준;이정훈
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.05a
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    • pp.27-30
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    • 2000
  • 본 논문에서는 선형 이진 신경회로망(Linear Binary Neural Network)을 이용하여 이진 영상으로부터 골격(skeleton)을 추출하는 병렬 구조를 제안하였다. 기존의 골격 추출 알고리즘으로부터 이진함수를 추출하고 이를 MSP Term Grouping Algorithm을 이용하여 학습시켰다. 결과에서는 기존의 역전파(Back-propagation) 학습알고리즘을 사용한 신경회로망보다 더 쉽게 하드웨어로 구현할 수 있음을 보여준다.

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