• Title/Summary/Keyword: Scale-invariant Feature

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Illumination invariant image matching using histogram equalization (히스토그램 평활화를 이용한 조명변화에 강인한 영상 매칭)

  • Oh, Changbeom;Kang, Minsung;Sohn, Kwanghoon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2011.11a
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    • pp.161-164
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    • 2011
  • 영상 매칭은 컴퓨터 비전에서 기초적인 기술로써 영상 추적, 물체인식 등 다양한 분양에서 많이 사용되고 있다. 하지만 스케일, 시점변화, 조명 변화에 강인한 매칭점을 찾는 것은 어려운 일이다. 이러한 문제점을 보완하기 위해 SURF(Scale Invariant Feature Transform), SIFT(Speed up Robust Features) 등의 알고리즘이 제안 되었지만, 여전히 조명변화에 불안정하고 정확하지 못한 성능을 보인다. 본 논문에서는 이러한 조명변화에 대한 문제점을 해결하기 위해 히스토그램 평활화를 이용하여 영상을 보정 후, SURF를 통한 영상 매칭을 하였다. 열악한 조명환경 내에서 촬영된 영상에서 SURF를 이용하여 표현자(Descriptor)를 생성 할 때 특징점이 잘 추출되지 않는 문제점을 해결하기 위하여 히스토그램 평활화를 이용하였고, 보정 후 특징점 개수가 많이 증가하는 것을 보여 확인하였다. 기존의 SURF와 개량된 SURF를 조명이 서로 다른 영상간의 매칭 성능을 비교함으로써 제안한 알고리즘의 우수성을 확인하였다

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Arctic Sea Ice Motion Measurement Using Time-Series High-Resolution Optical Satellite Images and Feature Tracking Techniques (고해상도 시계열 광학 위성 영상과 특징점 추적 기법을 이용한 북극해 해빙 이동 탐지)

  • Hyun, Chang-Uk;Kim, Hyun-cheol
    • Korean Journal of Remote Sensing
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    • v.34 no.6_2
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    • pp.1215-1227
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    • 2018
  • Sea ice motion is an important factor for assessing change of sea ice because the motion affects to not only regional distribution of sea ice but also new ice growth and thickness of ice. This study presents an application of multi-temporal high-resolution optical satellites images obtained from Korea Multi-Purpose Satellite-2 (KOMPSAT-2) and Korea Multi-Purpose Satellite-3 (KOMPSAT-3) to measure sea ice motion using SIFT (Scale-Invariant Feature Transform), SURF (Speeded Up Robust Features) and ORB (Oriented FAST and Rotated BRIEF) feature tracking techniques. In order to use satellite images from two different sensors, spatial and radiometric resolution were adjusted during pre-processing steps, and then the feature tracking techniques were applied to the pre-processed images. The matched features extracted from the SIFT showed even distribution across whole image, however the matched features extracted from the SURF showed condensed distribution of features around boundary between ice and ocean, and this regionally biased distribution became more prominent in the matched features extracted from the ORB. The processing time of the feature tracking was decreased in order of SIFT, SURF and ORB techniques. Although number of the matched features from the ORB was decreased as 59.8% compared with the result from the SIFT, the processing time was decreased as 8.7% compared with the result from the SIFT, therefore the ORB technique is more suitable for fast measurement of sea ice motion.

Automatic Target Recognition by selecting similarity-transform-invariant local and global features (유사변환에 불변인 국부적 특징과 광역적 특징 선택에 의한 자동 표적인식)

  • Sun, Sun-Gu;Park, Hyun-Wook
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.4
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    • pp.370-380
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    • 2002
  • This paper proposes an ATR (Automatic Target Recognition) algorithm for identifying non-occluded and occluded military vehicles in natural FLIR (Forward Looking InfraRed) images. After segmenting a target, a radial function is defined from the target boundary to extract global shape features. Also, to extract local shape features of upper region of a target, a distance function is defined from boundary points and a line between two extreme points. From two functions and target contour, four global and four local shape features are proposed. They are much more invariant to translation, rotation and scale transform than traditional feature sets. In the experiments, we show that the proposed feature set is superior to the traditional feature sets with respect to the similarity-transform invariance and recognition performance.

MPEG-7 Homogeneous Texture Descriptor

  • Ro, Yong-Man;Kim, Mun-Churl;Kang, Ho-Kyung;Manjunath, B.S.;Kim, Jin-Woong
    • ETRI Journal
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    • v.23 no.2
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    • pp.41-51
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    • 2001
  • MPEG-7 standardization work has started with the aims of providing fundamental tools for describing multimedia contents. MPEG-7 defines the syntax and semantics of descriptors and description schemes so that they may be used as fundamental tools for multimedia content description. In this paper, we introduce a texture based image description and retrieval method, which is adopted as the homogeneous texture descriptor in the visual part of the MPEG-7 final committee draft. The current MPEG-7 homogeneous texture descriptor consists of the mean, the standard deviation value of an image, energy, and energy deviation values of Fourier transform of the image. These are extracted from partitioned frequency channels based on the human visual system (HVS). For reliable extraction of the texture descriptor, Radon transformation is employed. This is suitable for HVS behavior. We also introduce various matching methods; for example, intensity-invariant, rotation-invariant and/or scale-invariant matching. This technique retrieves relevant texture images when the user gives a querying texture image. In order to show the promising performance of the texture descriptor, we take the experimental results with the MPEG-7 test sets. Experimental results show that the MPEG-7 texture descriptor gives an efficient and effective retrieval rate. Furthermore, it gives fast feature extraction time for constructing the texture descriptor.

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Feature Extraction Based on GRFs for Facial Expression Recognition

  • Yoon, Myoong-Young
    • Journal of Korea Society of Industrial Information Systems
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    • v.7 no.3
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    • pp.23-31
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    • 2002
  • In this paper we propose a new feature vector for recognition of the facial expression based on Gibbs distributions which are well suited for representing the spatial continuity. The extracted feature vectors are invariant under translation rotation, and scale of an facial expression imege. The Algorithm for recognition of a facial expression contains two parts: the extraction of feature vector and the recognition process. The extraction of feature vector are comprised of modified 2-D conditional moments based on estimated Gibbs distribution for an facial image. In the facial expression recognition phase, we use discrete left-right HMM which is widely used in pattern recognition. In order to evaluate the performance of the proposed scheme, experiments for recognition of four universal expression (anger, fear, happiness, surprise) was conducted with facial image sequences on Workstation. Experiment results reveal that the proposed scheme has high recognition rate over 95%.

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Integrated SIFT Algorithm with Feature Point Matching Filter for Relative Position Estimation (특징점 정합 필터 결합 SIFT를 이용한 상대 위치 추정)

  • Gwak, Min-Gyu;Sung, Sang-Kyung;Yun, Suk-Chang;Won, Dae-Hee;Lee, Young-Jae
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.8
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    • pp.759-766
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    • 2009
  • The purpose of this paper is an image processing algorithm development as a base research achieving performance enhancement of integrated navigation system. We used the SIFT (Scale Invariant Feature Transform) algorithm for image processing, and developed feature point matching filter for rejecting mismatched points. By applying the proposed algorithm, it is obtained better result than other methods of parameter tuning and KLT based feature point tracking. For further study, integration with INS and algorithm optimization for the real-time implementation are under investigation.

An Illumination-Insensitive Stereo Matching Scheme Based on Weighted Mutual Information (조명 변화에 강인한 상호 정보량 기반 스테레오 정합 기법)

  • Heo, Yong Seok
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.11
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    • pp.2271-2283
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    • 2015
  • In this paper, we propose a method which infers an accurate disparity map for radiometrically varying stereo images. For this end, firstly, we transform the input color images to the log-chromaticity color space from which a linear relationship can be established during constructing a joint pdf between input stereo images. Based on this linear property, we present a new stereo matching cost by combining weighted mutual information and the SIFT (Scale Invariant Feature Transform) descriptor with segment-based plane-fitting constraints to robustly find correspondences for stereo image pairs which undergo radiometric variations. Experimental results show that our method outperforms previous methods and produces accurate disparity maps even for stereo images with severe radiometric differences.

Image-based Image Retrieval System Using Duplicated Point of PCA-SIFT (PCA-SIFT의 차원 중복점을 이용한 이미지 기반 이미지 검색 시스템)

  • Choi, GiRyong;Jung, Hye-Wuk;Lee, Jee-Hyoung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.3
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    • pp.275-279
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    • 2013
  • Recently, as multimedia information becomes popular, there are many studies to retrieve images based on images in the web. However, it is hard to find the matching images which users want to find because of various patterns in images. In this paper, we suggest an efficient images retrieval system based on images for finding products in internet shopping malls. We extract features for image retrieval by using SIFT (Scale Invariant Feature Transform) algorithm, repeat keypoint matching in various dimension by using PCA-SIFT, and find the image which users search for by combining them. To verify efficiency of the proposed method, we compare the performance of our approach with that of SIFT and PCA-SIFT by using images with various patterns. We verify that the proposed method shows the best distinction in the case that product labels are not included in images.

Automatic Image-to-Image Registration of Middle- and Low-resolution Satellite Images Using Scale-Invariant Feature Transform Technique (SIFT 기법을 이용한 중.저해상도 위성영상간의 자동 기하보정)

  • Han, Dong-Yeob;Kim, Dae-Sung;Lee, Jae-Bin;Oh, Jae-Hong;Kim, Yong-Il
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.24 no.5
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    • pp.409-416
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    • 2006
  • To use image data obtained from different sensors and different techniques, the preprocessing step that registers them in a common coordinate system is needed. For this purpose, we developed the methodology to register middle- and low-resolution satellite images automatically. Firstly, candidate matching points were extracted using the Harris and Harris-affine algorithm. Secondly, we used the correlation coefficient, normalized correlation coefficient and SIFT algorithm to detect conjugate matching points from candidates. Then, to test the feasibility of approaches, we applied the developed methodology to various kinds of satellite images and compared results. The results clearly demonstrate that the methology using the SIFT is appropriate to register these multi-resolution satellite images automatically, compared with the classical cross-correlation.

The design and implementation of Object-based bioimage matching on a Mobile Device (모바일 장치기반의 바이오 객체 이미지 매칭 시스템 설계 및 구현)

  • Park, Chanil;Moon, Seung-jin
    • Journal of Internet Computing and Services
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    • v.20 no.6
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    • pp.1-10
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    • 2019
  • Object-based image matching algorithms have been widely used in the image processing and computer vision fields. A variety of applications based on image matching algorithms have been recently developed for object recognition, 3D modeling, video tracking, and biomedical informatics. One prominent example of image matching features is the Scale Invariant Feature Transform (SIFT) scheme. However many applications using the SIFT algorithm have implemented based on stand-alone basis, not client-server architecture. In this paper, We initially implemented based on client-server structure by using SIFT algorithms to identify and match objects in biomedical images to provide useful information to the user based on the recently released Mobile platform. The major methodological contribution of this work is leveraging the convenient user interface and ubiquitous Internet connection on Mobile device for interactive delineation, segmentation, representation, matching and retrieval of biomedical images. With these technologies, our paper showcased examples of performing reliable image matching from different views of an object in the applications of semantic image search for biomedical informatics.