A Novel Feature Detection Algorithm Based on Improved 2DPCA- SIFT

AiliWang,Yangyang Zhao,Jiaying Zhao,Yuji Iwahori,Xinyuan Wang 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.6

Stable local feature and representation is a fundamental component of many image registration, 3D reconstruction and object recognition algorithms. SIFT is a good descriptor that encodes the salient aspects of the image gradient in the feature point’s neighborhood. This paper improved SIFT- based local image descriptor and proposed a SIFT feature matching algorithm based on improved 2DPCA which can eliminate both rows and columns of relevance. Experimental results show that improved 2DPCA-SIFT algorithm is relatively stable, accurate and fast.

Multiple Vehicle Detection and Tracking in Highway Traffic Surveillance Video Based on SIFT Feature Matching

( Kenan Mu ),( Fei Hui ),( Xiangmo Zhao ) 한국정보처리학회 2016 Journal of information processing systems Vol.12 No.2

This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving vehicles can be detected by analyzing the difference image of the two aligned images. Vehicle tracking is also performed based on SIFT feature matching. For the decreasing of time consumption and maintaining higher tracking accuracy, the detected candidate vehicle in the current image is matched with the vehicle sample in the tracking sample set, which contains all of the detected vehicles in previous images. Most remarkably, the management of vehicle entries and exits is realized based on SIFT feature matching with an efficient update mechanism of the tracking sample set. This entire method is proposed for highway traffic environment where there are no nonautomotive vehicles or pedestrians, as these would interfere with the results.

Multiple Vehicle Detection and Tracking in Highway Traffic Surveillance Video Based on SIFT Feature Matching

Mu, Kenan,Hui, Fei,Zhao, Xiangmo Korea Information Processing Society 2016 Journal of information processing systems Vol.12 No.2

This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving vehicles can be detected by analyzing the difference image of the two aligned images. Vehicle tracking is also performed based on SIFT feature matching. For the decreasing of time consumption and maintaining higher tracking accuracy, the detected candidate vehicle in the current image is matched with the vehicle sample in the tracking sample set, which contains all of the detected vehicles in previous images. Most remarkably, the management of vehicle entries and exits is realized based on SIFT feature matching with an efficient update mechanism of the tracking sample set. This entire method is proposed for highway traffic environment where there are no non-automotive vehicles or pedestrians, as these would interfere with the results.

특징점 정합 필터 결합 SIFT를 이용한 상대 위치 추정

곽민규(Mingyu Gwak),성상경(Sangkyung Sung),윤석창(Sukchang Yun),원대희(Dae Hee Won),이영재(Young Jae Lee) 한국항공우주학회 2009 韓國航空宇宙學會誌 Vol.37 No.8

본 논문은 INS/vSLAM 통합 항법 시스템의 성능 향상을 위한 기초 연구로써, 비전 센서의 영상처리 성능을 향상을 위한 알고리즘 개발에 목표를 두고 있다. 비전센서의 영상처리 알고리즘으로 SIFT 알고리즘을 사용하였으며, SIFT 알고리즘의 특징점 정합 성능을 개선하기 위해 특징점 정합 필터를 적용하였다. 본 논문에서 제안한 알고리즘을 이용하여 기존의 SIFT 알고리즘을 파라미터 조절한 경우보다 향상된 결과를 얻을 수 있었다. 차후 실시간 통합 항법 시스템에 적용하기 위해서 알고리즘의 속도를 향상시키는 작업이 필요하다. 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.

SIFT-Based 3D Feature Matching and Reconstruction with Binocular Stereo Vision

Shuanghe Yu,Jialu Du,Siyuan Wang,He Xu 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8

In this paper, we address the problem of 3D (three-dimensional) feature matching and reconstruction method with SIFT(scale invariant feature transform)-based algorithm under binocular stereo vision. The technique is fulfilled by camera calibration, image processing, feature detection and 3D calculation. Zhang plane-based calibration and Harris corner point detection method are utilized for Camera calibration. SIFT algorithm is focused as feature extraction and matching algorithm to obtain the image coordinates of matching points. The obtained 3D coordinates are validated by the measurement results with a laser sensor. Finally the depth map of 3D environment is produced with the measured results. VC++.NET and OpenCV are used to compile the algorithm for the experiment in this research.

Oblique aerial image matching based on iterative simulation and homography evaluation

Song, Woo-Hyuck,Jung, Hong-Gyu,Gwak, In-Youb,Lee, Seong-Whan Elsevier 2019 Pattern recognition Vol.87 No.-

<P><B>Abstract</B></P> <P>This paper presents a fast and accurate method for matching oblique aerial image pairs. In order to achieve accurate matching results, we must consider viewpoint differences between the input images in addition to rotation and scaling. Existing methods that match aerial image pairs with viewpoint differences undergo heavy computation and have difficulty finding correspondences. In this paper, we propose a homography matrix evaluation method based on a geometric approach to increase the accuracy of image matching results. In addition, we achieve faster matching through an iterative transform simulation that reduces computational complexity. Experimental results show that the proposed method improves aerial image matching in terms of computational efficiency while achieving successful matching results.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Iterative transform simulation is proposed to reduce the computational complexity of image matching. </LI> <LI> A geometric method to evaluate the homography matrix is proposed to filter out wrong matching results. </LI> <LI> Superior performance in terms of speed while maintaining accuracy in matching oblique aerial images. </LI> </UL> </P>

An Implementation of Copy-Move Forgery Detector using SIFT-based Feature Refinement

황재정,이강현 대한전자공학회 2022 IEIE Transactions on Smart Processing & Computing Vol.11 No.1

This paper deals with refining the SIFT-based feature set for the Copy-Move forgery detection in image forensics. Many researchers attempt to extract the feature with advanced performance; however, high-dimensional feature sets increment the calculation cost and the detection time. For this reason, we intend to design a simple feature yet have good copy-move forgery detection performance. In addition to that, for various conditions of images, we extract the refined SIFT-based features of robust yet straightforward features applied to Copy-Move image forensics using only the SIFT features that have excellent invariance maintenance. In a Copy-Move forgery image, a definition has a similar distance and slope between a copy and move area. This paper proposed a new scheme for a Copy-Move forgery detection to satisfy the purpose. As a result, the Copy-Move area is detected with 97.8% upper. Thus, the detection ratio is confirmed as an 'Excellent (A)' grade.

SIFT를 이용한 장면전환 검출 및 필터링 기술

문원준,유인재,이재청,서영호,김동욱 한국방송∙미디어공학회 2019 방송공학회논문지 Vol.24 No.6

With the revitalization of the media market, the necessity of compression, searching, editing and copyright protection of videos is increasing. In this paper, we propose a method to detect scene change in all these fields. We propose a pre-processing, feature point extraction using SIFT, and matching algorithm for detecting the same scene change even if distortions such as resolution change, subtitle insertion, compression, and flip are added in the distribution process. Also, it is applied to filtering technology and it is confirmed that it is effective for all transformations other than considering transform.

컬러 불변 특징을 갖는 확장된 SURF 알고리즘

윤현섭(Hyun-Sup Yoon),한영준(Young-Joon Han),한헌수(Hyun-Sup Yoon) 한국컴퓨터정보학회 2009 한국컴퓨터정보학회 학술발표논문집 Vol.16 No.2

여러 개의 영상으로부터 스케일, 조명, 시점 등의 환경변화를 고려하여 대응점을 찾는 일은 쉽지 않다. SURF는 이러한 환경변화에 불변하는 특징점을 찾는 알고리즘중 하나로서 일반적으로 성능이 우수하다고 알려진 SIFT와 견줄만한 성능을 보이면서 속도를 크게 향상시킨 알고리즘이다. 하지만 SURF는 그레이공간 상의 정보만 이용함에 따라 컬러공간상에 주어진 많은 유용한 특징들을 활용하지 못한다. 본 논문에서는 강인한 컬러특정정보를 포함하는 확장된 SURF알고리즘을 제안한다. 제안하는 방법의 우수성은 다양한 조명환경과 시점변화에 따른 영상을 SIFT와 SURF 그리고 제안하는 컬러정보를 적용한 SURF알고리즘과 비교 실험을 통해 입증하였다.

A PTV Method Based on SIFT Feature Points Matching for Velocimetry Measurement of Oil-water Two-phase Flow in Horizontal Pipelines

Weihang Kong,Lei Li,Lingfu Kong,Yingwei Li,Na Xie 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.12

Due to the advantages of scale invariant feature transform (SIFT) feature points on the invariant to image scale, brightness, rotation, occlusion, noise and so on, this paper proposes a Particle Tracking Velocimetry (PTV) method, based on SIFT feature points matching for velocity measurement of oil-water two-phase flow in horizontal pipelines. The oil-water two-phase flow with large droplet diameter, oil droplets overlap, ununiform lighting, and the centroid position of oil droplets can’t be obtained only by using traditional PTV methods through morphological processing. However, in this paper, the algorithm can directly achieve the average velocity of the flow field according to the positions of correctly matched SIFT feature points, and there is no need to extract the centroid coordinates of each oil droplet. The experimental results show that the proposed algorithm not only can be used in the average velocity measurement of oil-water two-phase flow in horizontal pipelines, but also can reach 95% in the measuring accuracy when the matching feature points are enough sufficient.