• Title/Summary/Keyword: Thinning Algorithm

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A study on crack detection using Image processing (화상처리 기법을 이용한 균열 검출에 관한 연구)

  • 이방연;김진근;박석균
    • Proceedings of the Korea Concrete Institute Conference
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    • 2003.11a
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    • pp.655-658
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    • 2003
  • The crack of concrete structure plays an important role in the durability and safety of structure. Therefore, the features such as width, length, and direction of that must be measured periodically. The conventional method of measurement of cracks is manually sketched, however. it takes a fairly long time and lacks quantitative objectivity. This study proposes the algorithm to extract and analyze cracks automatically. The proposed algorithm is composed of two sub-algorithms. The extraction algorithm includes elimination of effect due to light, binarization. and noise reduction. The analysis algorithm includes thinning process, labeling, and calculation of crack width, length, and direction. The test to demonstrate the algorithm is fulfilled using the images of cracks on real concrete surface.

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A-Modified Thinning Algorithm using the 4-Neighbors Connection Value for the Character Recognition (수정된 4-이웃 연결값을 이용한 세선화 알고리즘)

  • 원남식
    • Journal of Korea Society of Industrial Information Systems
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    • v.7 no.1
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    • pp.50-57
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    • 2002
  • This paper is the study about the improvement of the WPTA4 algorithm available for the recognition of various characters. The WPTA4 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 the WPTA4 and propose an modified algorithm which can eliminate this phenomena. The proposed algorithm shows that the skeleton disappearance phenomena is eliminated and the quality of extracted skeleton is excellent.

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High Speed and Low Power Scheme for a Fingerprint Identification Algorithm (고속 저전력 지문인식 알고리즘 처리용 회로)

  • Yoo, Min-Hee;Jung, Seung-Min
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.111-114
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    • 2008
  • This paper proposes an effective hardware scheme for gabor filter and thinning stage processing of a fingerprint identification algorithm based on minutiae with 80% cycle occupation of 32-bit RISC microprocessor. The algorithm was developed based on minutiae with bifurcation and ending point. The analysis of an algorithm source rode was performed using ARM emulator.

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Image Processing Algorithms for Non-destructive Testing

  • Lee, SangBock
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.9
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    • pp.45-49
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    • 2016
  • In this study, an image processing algorithm was developed to increase readability of the images of specific parts of a KTX train acquired by using a mobile digital radiographic testing device in a situation where a running train is stopped. The image processing algorithm was realized by using a Visual C++ development tool. The algorithm developed in this study allows to select an interested region in the acquired images when the interested region is suspected to cause a problem, and applies a thinning process based Sobel operators to the selected region. The experimental results show that the readability of defect parts that are not visible to naked eyes was increased through edge detector. Application of the algorithm developed in this study may help to accurately read non-destructive inspection images.

A Study on the Automatic Classification between Contour Elements and Non-Contour Elements in a Contour Map Image (등고선 지도영상에서의 등고 성분과 비등고 성분의 자동 분리에 관한 연구)

  • 김경훈;김준식
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.4
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    • pp.7-16
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    • 2002
  • En this paper, we propose the algorithm that has analyzed the map Information automatically to extract the contour lines and numbers, symbols from the map image. After converting the input image to binary one, thinned image is obtained by thinning algorithm. The contour elements in the thinned image are classified and the classified elements are analyzed to automatically classify the numbers from symbols. Finally, the broken parts are restored by reconstruction algorithm. The performance of proposed algorithm is verified through the simulation. The proposed one has good performance.

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Fingerprint Pattern Recognition Algorithm (지문 Pattern 인식 Algorithm)

  • 김정규;김봉일
    • Korean Journal of Remote Sensing
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    • v.3 no.1
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    • pp.25-39
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    • 1987
  • The purpose of this research is to develop the Automatic Fingerprint Verfication System by digital computer based on specially in PC level. Fingerprint is used as means of personal identity verification in view of that it has the high reliability and safety. Fingerprint pattern recognition algorithm is constitute of 3 stages, namely of the preprocessing, the feature extraction and the recognition. The preprocessing stage includes smoothing, binarization, thinning and restoration. The feature extraction stage includes the extraction of minutiae and its features. The recognition stage includes the registration and the matching score calculation which measures the similarity between two images. Tests for this study with 325 pairs of fingerprint resulted in 100% of separation which which in turn is turned out to be the reliability of this algorithm.

A Vehicle License Plate Recognition Using the Feature Vectors based on Mesh and Thinning (메쉬 및 세선화 기반 특징 벡터를 이용한 차량 번호판 인식)

  • Park, Seung-Hyun;Cho, Seong-Won
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.705-711
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    • 2011
  • This paper proposes an effective algorithm of license plate recognition for industrial applications. By applying Canny edge detection on a vehicle image, it is possible to find a connected rectangular, which is a strong candidate for license plate. The color information of license plate separates plates into white and green. Then, OTSU binary image processing and foreground neighbor pixel propagation algorithm CLNF will be applied to each license plates to reduce noise except numbers and letters. Finally, through labeling, numbers and letters will be extracted from the license plate. Letter and number regions, separated from the plate, pass through mesh method and thinning process for extracting feature vectors by X-Y projection method. The extracted feature vectors are compared with the pre-learned weighting values by backpropagation neural network to execute final recognition process. The experiment results show that the proposed license plate recognition algorithm works effectively.

A study on the design of an efficient hardware and software mixed-mode image processing system for detecting patient movement (환자움직임 감지를 위한 효율적인 하드웨어 및 소프트웨어 혼성 모드 영상처리시스템설계에 관한 연구)

  • Seungmin Jung;Euisung Jung;Myeonghwan Kim
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.29-37
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    • 2024
  • In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

Statistical Edge Detecting Method Using a New operator. (새로운 연산자를 이용한 통계적인 윤곽선 추출기법)

  • Lee, Hae-Young;Kim, Hoon-Hak;Lee, Keun-Young
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1394-1397
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    • 1987
  • It is difficult to detect edge segments from a noisy image since the image have a noise in piratical applications which utilize some type of visual input capability. Hence, the proposed algorithm consists of the modality tests based on parallel statistical tests without a noise removal preprocessing or postprocessing, and the edge detection technique With one-Pixel edge segments in this paper. The algorithm is very reliable and effective in the case of those situations where the Picture is poor quality and low resolution. And it does'nt require thinning operation and thresholding in hand. Experimental comparision With the more conventional techniques when applied to typical low-quality Pictures confirms good capabilities of the algorithm.

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Automatic Real-time Identification of Fingerprint Images Using Block-FFT (블럭 FFT를 이용한 실시간 지문 인식 알고리즘)

  • 안도성;김학일
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.6
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    • pp.909-921
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    • 1995
  • The objective of this paper is to develop an algorithm for a real-time automatic fingerprint recognition system. The algorithm employs the Fast Fourier Transform (FFT) in determining the directions of ridges in fingerprint images, and utilizes statistical information in recognizing the fingerprints. The information used in fingerprint recognition is based on the dircetions along ridge curves and characteristic points such as core points and delta points. In order to find ridge directions, the algorithm applies the FFT to a small block of the size 8x8 pixels, and decides the directions by interpreting the resulted Fourier spectrum. By using the FFT, the algorithm does not require conventional preprocessing procedures such as smoothing, binarization, thinning, and restorationl. Finally, in matching two fingerprint images, the algorithm searches and compares two kinds of feature blocks, one as the blocks where the dircetions cannot be defined from the Fourier spectrum, and the other as the blocks where the changes of directions become abrupt. The proposed algorithm has been implemented on a SunSparc-2 workstation under the Open Window environment. In the experiment, the proposed algorithm has been applied to a set of fingerprint images obtained by a prism system. The result has shown that while the rate of Type II error - Incorrect recognition of two different fingerprints as the identical fingerprints - is held at 0.0%, the rate of Type I error - Incorrect recognition of two identical fingerprints as the different ones - is 2.2%.

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