• Title/Summary/Keyword: Feature Point Extraction and Matching

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INTERACTIVE FEATURE EXTRACTION FOR IMAGE REGISTRATION

  • Kim Jun-chul;Lee Young-ran;Shin Sung-woong;Kim Kyung-ok
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.641-644
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    • 2005
  • This paper introduces an Interactive Feature Extraction (!FE) approach for the registration of satellite imagery by matching extracted point and line features. !FE method contains both point extraction by cross-correlation matching of singular points and line extraction by Hough transform. The purpose of this study is to minimize user's intervention in feature extraction and easily apply the extracted features for image registration. Experiments with these imagery dataset proved the feasibility and the efficiency of the suggested method.

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A Method to Adjust Cyclic Signal Length Using Time Invariant Feature Point Extraction and Matching(TIFEM) (시불변 특징점 추출 및 정합을 이용한 주기 신호의 길이 보정 기법)

  • Han, A-Hyang;Park, Cheong-Sool;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of the Korea Society for Simulation
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    • v.19 no.4
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    • pp.111-122
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    • 2010
  • In this study, a length adjustment algorithm for cyclic signals in manufacturing process using Time Invariant Feature point Extraction and Matching(TIFEM) is proposed. In order to precisely compensate the length of cyclic signals which have irregular length in the middle of signal as well as in the full length more feature points are needed. The extracted feature must involve information about the pattern of signal and should have invariant properties on time and scale. The proposed TIFEM algorithm extracts features having the intrinsic properties of the signal characteristics at first. By using those extracted features, feature vector is constructed for each time point. Among those extracted features, the only effective features are filtered and are chosen such as basis for the length adjustment. And then the partial length adjustment is performed by matching feature points. To verify the performance of the proposed algorithm, the experiments were performed with the experimental data mimicking the three kinds of signals generated from the actual semiconductor process.

Feature Extraction for Endoscopic Image by using the Scale Invariant Feature Transform(SIFT) (SIFT를 이용한 내시경 영상에서의 특징점 추출)

  • Oh, J.S.;Kim, H.C.;Kim, H.R.;Koo, J.M.;Kim, M.G.
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.6-8
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    • 2005
  • Study that uses geometrical information in computer vision is lively. Problem that should be preceded is matching problem before studying. Feature point should be extracted for well matching. There are a lot of methods that extract feature point from former days are studied. Because problem does not exist algorithm that is applied for all images, it is a hot water. Specially, it is not easy to find feature point in endoscope image. The big problem can not decide easily a point that is predicted feature point as can know even if see endoscope image as eyes. Also, accuracy of matching problem can be decided after number of feature points is enough and also distributed on whole image. In this paper studied algorithm that can apply to endoscope image. SIFT method displayed excellent performance when compared with alternative way (Affine invariant point detector etc.) in general image but SIFT parameter that used in general image can't apply to endoscope image. The gual of this paper is abstraction of feature point on endoscope image that controlled by contrast threshold and curvature threshold among the parameters for applying SIFT method on endoscope image. Studied about method that feature points can have good distribution and control number of feature point than traditional alternative way by controlling the parameters on experiment result.

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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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Hierarchical stereo matching using feature extraction of an image

  • Kim, Tae-June;Yoo, Ji-Sang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.99-102
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    • 2009
  • In this paper a hierarchical stereo matching algorithm based on feature extraction is proposed. The boundary (edge) as feature point in an image is first obtained by segmenting an image into red, green, blue and white regions. With the obtained boundary information, disparities are extracted by matching window on the image boundary, and the initial disparity map is generated when assigned the same disparity to neighbor pixels. The final disparity map is created with the initial disparity. The regions with the same initial disparity are classified into the regions with the same color and we search the disparity again in each region with the same color by changing block size and search range. The experiment results are evaluated on the Middlebury data set and it show that the proposed algorithm performed better than a phase based algorithm in the sense that only about 14% of the disparities for the entire image are inaccurate in the final disparity map. Furthermore, it was verified that the boundary of each region with the same disparity was clearly distinguished.

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Image Feature Point Selection Method Using Nearest Neighbor Distance Ratio Matching (최인접 거리 비율 정합을 이용한 영상 특징점 선택 방법)

  • Lee, Jun-Woo;Jeong, Jea-Hyup;Kang, Jong-Wook;Na, Sang-Il;Jeong, Dong-Seok
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.12
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    • pp.124-130
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    • 2012
  • In this paper, we propose a feature point selection method for MPEG CDVS CE-7 which is processing on International Standard task. Among a large number of extracted feature points, more important feature points which is used in image matching should be selected for the compactness of image descriptor. The proposed method is that remove the feature point in the extraction phase which is filtered by nearest neighbor distance ratio matching in the matching phase. We can avoid the waste of the feature point and employ additional feature points by the proposed method. The experimental results show that our proposed method can obtain true positive rate improvement about 2.3% in pair-wise matching test compared with Test Model.

An Efficient Feature Point Extraction Method for 360˚ Realistic Media Utilizing High Resolution Characteristics

  • Won, Yu-Hyeon;Kim, Jin-Sung;Park, Byuong-Chan;Kim, Young-Mo;Kim, Seok-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.1
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    • pp.85-92
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    • 2019
  • In this paper, we propose a efficient feature point extraction method that can solve the problem of performance degradation by introducing a preprocessing process when extracting feature points by utilizing the characteristics of 360-degree realistic media. 360-degree realistic media is composed of images produced by two or more cameras and this image combining process is accomplished by extracting feature points at the edges of each image and combining them into one image if they cover the same area. In this production process, however, the stitching process where images are combined into one piece can lead to the distortion of non-seamlessness. Since the realistic media of 4K-class image has higher resolution than that of a general image, the feature point extraction and matching process takes much more time than general media cases.

Fast Stitching Algorithm by using Feature Tracking (특징점 추적을 통한 다수 영상의 고속 스티칭 기법)

  • Park, Siyoung;Kim, Jongho;Yoo, Jisang
    • Journal of Broadcast Engineering
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    • v.20 no.5
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    • pp.728-737
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    • 2015
  • Stitching algorithm obtain a descriptor of the feature points extracted from multiple images, and create a single image through the matching process between the each of the feature points. In this paper, a feature extraction and matching techniques for the creation of a high-speed panorama using video input is proposed. Features from Accelerated Segment Test(FAST) is used for the feature extraction at high speed. A new feature point matching process, different from the conventional method is proposed. In the matching process, by tracking region containing the feature point through the Mean shift vector required for matching is obtained. Obtained vector is used to match the extracted feature points. In order to remove the outlier, the RANdom Sample Consensus(RANSAC) method is used. By obtaining a homography transformation matrix of the two input images, a single panoramic image is generated. Through experimental results, we show that the proposed algorithm improve of speed panoramic image generation compared to than the existing method.

Classification of Feature Points Required for Multi-Frame Based Building Recognition (멀티 프레임 기반 건물 인식에 필요한 특징점 분류)

  • Park, Si-young;An, Ha-eun;Lee, Gyu-cheol;Yoo, Ji-sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.3
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    • pp.317-327
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    • 2016
  • The extraction of significant feature points from a video is directly associated with the suggested method's function. In particular, the occlusion regions in trees or people, or feature points extracted from the background and not from objects such as the sky or mountains are insignificant and can become the cause of undermined matching or recognition function. This paper classifies the feature points required for building recognition by using multi-frames in order to improve the recognition function(algorithm). First, through SIFT(scale invariant feature transform), the primary feature points are extracted and the mismatching feature points are removed. To categorize the feature points in occlusion regions, RANSAC(random sample consensus) is applied. Since the classified feature points were acquired through the matching method, for one feature point there are multiple descriptors and therefore a process that compiles all of them is also suggested. Experiments have verified that the suggested method is competent in its algorithm.

Genetic lesion matching algorithm using medical image (의료영상 이미지를 이용한 유전병변 정합 알고리즘)

  • Cho, Young-bok;Woo, Sung-Hee;Lee, Sang-Ho;Han, Chang-Su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.5
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    • pp.960-966
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    • 2017
  • In this paper, we proposed an algorithm that can extract lesion by inputting a medical image. Feature points are extracted using SIFT algorithm to extract genetic training of medical image. To increase the intensity of the feature points, the input image and that raining image are matched using vector similarity and the lesion is extracted. The vector similarity match can quickly lead to lesions. Since the direction vector is generated from the local feature point pair, the direction itself only shows the local feature, but it has the advantage of comparing the similarity between the other vectors existing between the two images and expanding to the global feature. The experimental results show that the lesion matching error rate is 1.02% and the processing speed is improved by about 40% compared to the case of not using the feature point intensity information.