• Title/Summary/Keyword: Image edge extraction

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Virtual core point detection and ROI extraction for finger vein recognition (지정맥 인식을 위한 가상 코어점 검출 및 ROI 추출)

  • Lee, Ju-Won;Lee, Byeong-Ro
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.3
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    • pp.249-255
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    • 2017
  • The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

A study on range image segmentation and surface feature extraction (거리 영상 분할과 면 특징 추출에 관한 연구)

  • 현대환;김대현;이선호;최종수
    • Proceedings of the Korean Information Science Society Conference
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    • 1999.10b
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    • pp.509-511
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    • 1999
  • 본 논문에서는 일반적으로 영역 기반형 분할방법보다 우수한 분할결과와 계산의 효율성을 가지는 경계선 기반형 방법의 하나인 scan line approximation 방법을 응용함으로써 경계선의 기하학적 해석이 가능하도록 하는 경계선 강도(edge intensity) 정보를 제공한다. 따라서 면 특성과 국부적인 면 특성인 면 법선과 면 곡률정보 없이 잡음에 강건하고 계산의 효율성에서 우수한 거리영상분할 방법을 제안한다. 합성 거리영상을 대상으로 scan line approximation 방법을 응용하여 얻어진 경계선을 경계선 그룹화의 영역 레이블링을 거쳐서 면 특징을 추출하였다.

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Effect of Calcium Carbonate on Properties of Paper in Alkali Paper Masking (중성초지에서 탄산칼슘의 성질이 종이의 물성에 미치는 영향)

  • 신종순
    • Journal of the Korean Graphic Arts Communication Society
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    • v.8 no.1
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    • pp.71-87
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    • 1990
  • This paper presents a simple algorithm to obtain three dimensional information of an object. In the preprocessing of the stereo matching,feature point informations of stero image must be less sensitive to noise and well liked the correspondance problem. This paper described a simple technique of struture feature extraction of 3-D object and used edge-end point expanding method for unconnected line instade of Hough transform. The feature such as corner point and their angles are used for matching problem. The experimental results show that the described algorithm is a useful method for stereo correspondence problem.

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Improvement of Mid-Wave Infrared Image Visibility Using Edge Information of KOMPSAT-3A Panchromatic Image (KOMPSAT-3A 전정색 영상의 윤곽 정보를 이용한 중적외선 영상 시인성 개선)

  • Jinmin Lee;Taeheon Kim;Hanul Kim;Hongtak Lee;Youkyung Han
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1283-1297
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    • 2023
  • Mid-wave infrared (MWIR) imagery, due to its ability to capture the temperature of land cover and objects, serves as a crucial data source in various fields including environmental monitoring and defense. The KOMPSAT-3A satellite acquires MWIR imagery with high spatial resolution compared to other satellites. However, the limited spatial resolution of MWIR imagery, in comparison to electro-optical (EO) imagery, constrains the optimal utilization of the KOMPSAT-3A data. This study aims to create a highly visible MWIR fusion image by leveraging the edge information from the KOMPSAT-3A panchromatic (PAN) image. Preprocessing is implemented to mitigate the relative geometric errors between the PAN and MWIR images. Subsequently, we employ a pre-trained pixel difference network (PiDiNet), a deep learning-based edge information extraction technique, to extract the boundaries of objects from the preprocessed PAN images. The MWIR fusion imagery is then generated by emphasizing the brightness value corresponding to the edge information of the PAN image. To evaluate the proposed method, the MWIR fusion images were generated in three different sites. As a result, the boundaries of terrain and objects in the MWIR fusion images were emphasized to provide detailed thermal information of the interest area. Especially, the MWIR fusion image provided the thermal information of objects such as airplanes and ships which are hard to detect in the original MWIR images. This study demonstrated that the proposed method could generate a single image that combines visible details from an EO image and thermal information from an MWIR image, which contributes to increasing the usage of MWIR imagery.

Extraction of Car License Plate Region Using Histogram Features of Edge Direction (에지 영상의 방향성분 히스토그램 특징을 이용한 자동차 번호판 영역 추출)

  • Kim, Woo-Tae;Lim, Kil-Taek
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.3
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    • pp.1-14
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    • 2009
  • In this paper, we propose a feature vector and its applying method which can be utilized for the extraction of the car license plate region. The proposed feature vector is extracted from direction code histogram of edge direction of gradient vector of image. The feature vector extracted is forwarded to the MLP classifier which identifies character and garbage and then the recognition of the numeral and the location of the license plate region are performed. The experimental results show that the proposed methods are properly applied to the identification of character and garbage, the rough location of license plate, and the recognition of numeral in license plate region.

Feature Extraction of Welds from Industrial Computed Radiography Using Image Analysis and Local Statistic Line-Clustering (산업용 CR 영상분석과 국부확률 선군집화에 의한 용접특징추출)

  • Hwang, Jung-Won;Hwang, Jae-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.5
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    • pp.103-110
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    • 2008
  • A reliable extraction of welded area is the precedent task before the detection of weld defects in industrial radiography. This paper describes an attempt to detect and extract the welded features of steel tubes from the computed radiography(CR) images. The statistical properties are first analyzed on over 160 sample radiographic images which represent either weld or non-weld area to identify the differences between them. The analysis is then proceeded by pattern classification to determine the clustering parameters. These parameters are the width, the functional match, and continuity. The observed weld image is processed line by line to calculate these parameters for each flexible moving window in line image pixel set. The local statistic line-clustering method is used as the classifier to recognize each window data as weld or non-weld cluster. The sequential procedure is to track the edge lines between two distinct regions by iterative calculation of threshold, and it results in extracting the weld feature. Our methodology is concluded to be effective after experiment with CR weld images.

Image Filter Optimization Method based on common sub-expression elimination for Low Power Image Feature Extraction Hardware Design (저전력 영상 특징 추출 하드웨어 설계를 위한 공통 부분식 제거 기법 기반 이미지 필터 하드웨어 최적화)

  • Kim, WooSuk;Lee, Juseong;An, Ho-Myoung;Kim, Byungcheul
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.2
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    • pp.192-197
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    • 2017
  • In this paper, image filter optimization method based on common sub-expression elimination is proposed for low-power image feature extraction hardware design. Low power and high performance object recognition hardware is essential for industrial robot which is used for factory automation. However, low area Gaussian gradient filter hardware design is required for object recognition hardware. For the hardware complexity reduction, we adopt the symmetric characteristic of the filter coefficients using the transposed form FIR filter hardware architecture. The proposed hardware architecture can be implemented without degradation of the edge detection data quality since the proposed hardware is implemented with original Gaussian gradient filtering algorithm. The expremental result shows the 50% of multiplier savings compared with previous work.

Object Detection Method in Sea Environment Using Fast Region Merge Algorithm (해양환경에서 고속 영역 병합 알고리즘을 이용한 물표 탐지 기법)

  • Jeong, Jong-Myeon;Park, Gyei-Kark
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.5
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    • pp.610-616
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    • 2012
  • In this paper, we present a method to detect an object such as ship, rock and buoy from sea IR image for the safety navigation. To this end, we do the image smoothing first and the apply watershed algorithm to segment image into subregions. Since watershed algorithm almost always produces over-segmented regions, it requires posterior merging process to get meaningful segmented regions. We propose an efficient merger algorithm that requires only two times of direct access to the pixels regardless of the number of regions. Also by analyzing IR image obtained from sea environments, we could find out that most horizontal edge come out from object regions. For the given input IR image we extract horizontal edge and eliminate isolated edges produced from background and noises by adopting morphological operator. Among the segmented regions, the regions that have horizontal edges are extracted as final results. Experimental results show the adequacy of the proposed method.

Image Identifier based on Local Feature's Histogram and Acceleration Technique using GPU (지역 특징 히스토그램 기반 영상식별자와 GPU 가속화)

  • Jeon, Hyeok-June;Seo, Yong-Seok;Hwang, Chi-Jung
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.9
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    • pp.889-897
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    • 2010
  • Recently, a cutting-edge large-scale image database system has demanded these attributes: search with alarming speed, performs with high accuracy, archives efficiently and much more. An image identifier (descriptor) is for measuring the similarity of two images which plays an important role in this system. The extraction method of an image identifier can be roughly classified into two methods: a local and global method. In this paper, the proposed image identifier, LFH(Local Feature's Histogram), is obtained by a histogram of robust and distinctive local descriptors (features) constrained by a district sub-division of a local region. Furthermore, LFH has not only the properties of a local and global descriptor, but also can perform calculations at a magnificent clip to determine distance with pinpoint accuracy. Additionally, we suggested a way to extract LFH via GPU (OpenGL and GLSL). In this experiment, we have compared the LFH with SIFT (local method) and EHD (global method) via storage capacity, extraction and retrieval time along with accuracy.

Feature Extraction for Scene Change Detection in an MPEG Video Sequence (장면 전환 검출을 위한 MPEG 비디오 시퀀스로부터 특징 요소 추출)

  • 최윤석;곽영경;고성제
    • Journal of Broadcast Engineering
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    • v.3 no.2
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    • pp.127-137
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    • 1998
  • In this paper, we propose the method of extracting edge information from MPEG video sequences for the detection of scene changes. In a the proposed method, five significant AC coefficients of each MPEG block are utilized to obtain edge images from the MPEG video. AC edge images obtained by the proposed scheme not only produce better object boundary information than conventional methods using only DC coefficients, but also can reduce the boundary effects produced by DC-based. Since the AC edge image contains the content information of each frame, it can be effectively utilized for the detection of scene change as well as the content-based video query. Experimental results show that the proposed method can be effectively utilized for the detection of scene changes.

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