• Title/Summary/Keyword: Image Thinning

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A Hardware Architecture for Retaining the Connectivity in Gray - Scale Image (그레이 레벨 연결성 복원 하드웨어 구조)

  • 김성훈;양영일
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.974-977
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    • 1999
  • In this paper, we have proposed the hardware architecture which implements the algorithm for retaining the connectivity which prevents disconnecting in the gray-scale image thinning To perform the image thinning in a real time which find a skeleton in image, it is necessary to examine the connectivity of the skeleton in a real time. The proposed architecture finds the connectivity number in the 4-clock period. The architecture is consists of three blocks, PS(Parallel to Serial) Converter and State Generator and Ridge Checker. The PS Converter changes the 3$\times$3 gray level image to four sets of image pixels. The State Generator examine the connectivity of the central pixel by searching the data from the PS Converter. the 3$\times$3 gray level image determines. The Ridge Checker determines whether the central pixel is on the skeleton or not The proposed architecture finds the connectivity of the central pixel in a 3$\times$3 gray level image in the 4-clocks. The total circuits are verified by the design tools and operate correctly.

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An Extraction Technique of Automatic Recognizing Regions on Power Distribution Facility Map by Partial Extension (부분확장에 의한 배전설비도면의 자동인식 대상영역 추출 방법)

  • Kim, Gye-Young;Lee, Bong-Jae;Cho, Seon-Ku;Woo, Hee-Gon
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.48 no.10
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    • pp.1349-1355
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    • 1999
  • A power distribution facility map is drawn on cadastral map. Besides, grid lines are added on the map for sectionalization. For automatic recognition of the map, we first extract recognizing regions. In this paper, we propose an extraction method of recognizing regions by partially extending thinned image. The proposed method is consist of three phases, binarization phase, thinning phase and partial extending phase. The first phase generate a binary image using threshold value which is obtained by histogram analysis. The binary image contains many part of recognizing regions, but not all. The second phase generate thinned image which is generated by appling thinning operator to the binary image. And the third phase extends thinned image from terminal point until satisfying termination condition. The proposed method is tested on several power distribution facility maps, and the results are presented.

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Spatial Images toward Thinning Systems on Larix Forest Stands (낙엽송 간벌 임분의 공간 이미지 분석)

  • Song, Hyung Sop;Myung, Jae Gab;Park, Min Woo;Son, Jong Eun;Yee, Sun
    • Korean Journal of Agricultural Science
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    • v.27 no.1
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    • pp.5-12
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    • 2000
  • The main purpose of this study is to obtain spatial image information toward forest thinning process in Larix forest stands. Thirteen different alternatives were simulated to visualize on the basis of actual thinning work photos. The options were illustrated as photos produced by photoshop program. Each alternatives were evaluated by forest visitor group with total 244 respondents after reliability test. Spatial images of 13 thinning photos were measured by 12 semantic differential scale as broad -narrow, ordered-tangled, friendly-unfriendly, monotonous-divers, dry-refreshing, relieved -stifling, healthy-sickly, uniform-scattered, dead-alive, opened-closed, bent-straight, and beautiful-ugly. In comparison with thinning stands and natural stands, thinning works were visual improvement effects of spatial images. Seemingly, this trend is due to definite form beauty, straight and clear length form of coniferous forest, As can be expected, slash and downwood were negatively related to improvement effects of spatial images. The 60% ratio of stem/ tree height and 450-950 trees/ha was positive in attraction of spatial images. Results indicate how to conduct forest thinning system for spatial images on Larix forest stands.

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Recognition of Zip-Code using Neural Network (신경 회로망을 이용한 우편번호 인식)

  • 이래경;김성신
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.365-365
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    • 2000
  • In this paper, we describe the system to recognize the six digit postal number of mails using neural network. Our zip-code recognition system consists of a preprocessing procedure for the original captured image, a segmentation procedure for separating an address block area with a shape, and recognition procedure for the cognition of a postal number. we extract the feature vectors that are the input of a neural network for the recognition process based on an area optimizing and an image thinning processing. The neural network classifies the zip-code in the mail and the recognized zip-code is verified through the zip-code database.

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Run Representation Based Minutiae Extraction in Fingerprint (수평과 수직 Run 표현을 이용한 지문영상에서의 minutiae 추출)

  • 황희연;신정환;이준재;진성일
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.65-68
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    • 2002
  • In an automatic fingerprint recognition system, a thinning process after binarization is commonly used. However it gives rise to spurs and holes often causing many spurious minutiae. Thus, more elaborate postprocessing is urgently needed to remove such spurious minutiae. To overcome this problem, we present a method of extracting minutiae based on horizontal and vertical run-length encoding from a binary fingerprint image without thinning process. Experimental results show that the proposed method for extracting minutiae is fairly reliable and fast, when il is compared to other method adopting a thinning process.

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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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A Robust Thinnig Algorithm (잡음에 강한 세선화 알고리즘)

  • 손동일;권영빈
    • Korean Journal of Cognitive Science
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    • v.2 no.2
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    • pp.341-358
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    • 1990
  • In this paper, A thinning algorithm which can solve a noise problem os proposed. The proposed method is based on the pavlidis thinning algorithm. During a contour tracing period of the given image, the masks of $3{\times}3$ pixels are proposed. They check all possible caseds of the noise conditions. As soon as the contour tracing is finished, the candidates of the noise are automatically deleted. As a result of the implementation of the proposed algorithm, the similar results which is obtained by noise-free image are obtained and they show the simplified structures comparing with the thinning results of the noisy images. Thus, They illustrate that a simple recognition part is needed to identify the objects.

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.

Extraction of Individual Trees and Tree Heights for Pinus rigida Forests Using UAV Images (드론 영상을 이용한 리기다소나무림의 개체목 및 수고 추출)

  • Song, Chan;Kim, Sung Yong;Lee, Sun Joo;Jang, Yong Hwan;Lee, Young Jin
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1731-1738
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    • 2021
  • The objective of this study was to extract individual trees and tree heights using UAV drone images. The study site was Gongju national university experiment forest, located in Yesan-gun, Chungcheongnam-do. The thinning intensity study sites consisted of 40% thinning, 20% thinning, 10% thinning and control. The image was filmed by using the "Mavic Pro 2" model of DJI company, and the altitude of the photo shoot was set at 80% of the overlay between 180m pictures. In order to prevent image distortion, a ground reference point was installed and the end lap and side lap were set to 80%. Tree heights were extracted using Digital Surface Model (DSM) and Digital Terrain Model (DTM), and individual trees were split and extracted using object-based analysis. As a result of individual tree extraction, thinning 40% stands showed the highest extraction rate of 109.1%, while thinning 20% showed 87.1%, thinning 10% showed 63.5%, and control sites showed 56.0% of accuracy. As a result of tree height extraction, thinning 40% showed 1.43m error compared with field survey data, while thinning 20% showed 1.73 m, thinning 10% showed 1.88 m, and control sites showed the largest error of 2.22 m.

STRONG k-DEFORMATION RETRACT AND ITS APPLICATIONS

  • Han, Sang-Eon
    • Journal of the Korean Mathematical Society
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    • v.44 no.6
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    • pp.1479-1503
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    • 2007
  • In this paper, we study a strong k-deformation retract derived from a relative k-homotopy and investigate its properties in relation to both a k-homotopic thinning and the k-fundamental group. Moreover, we show that the k-fundamental group of a wedge product of closed k-curves not k-contractible is a free group by the use of some properties of both a strong k-deformation retract and a digital covering. Finally, we write an algorithm for calculating the k-fundamental group of a dosed k-curve by the use of a k-homotopic thinning.