• Title/Summary/Keyword: Feature-based Matching

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PPD: A Robust Low-computation Local Descriptor for Mobile Image Retrieval

  • Liu, Congxin;Yang, Jie;Feng, Deying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.3
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    • pp.305-323
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    • 2010
  • This paper proposes an efficient and yet powerful local descriptor called phase-space partition based descriptor (PPD). This descriptor is designed for the mobile image matching and retrieval. PPD, which is inspired from SIFT, also encodes the salient aspects of the image gradient in the neighborhood around an interest point. However, without employing SIFT's smoothed gradient orientation histogram, we apply the region based gradient statistics in phase space to the construction of a feature representation, which allows to reduce much computation requirements. The feature matching experiments demonstrate that PPD achieves favorable performance close to that of SIFT and faster building and matching. We also present results showing that the use of PPD descriptors in a mobile image retrieval application results in a comparable performance to SIFT.

A Low Complexity, Descriptor-Less SIFT Feature Tracking System

  • Fransioli, Brian;Lee, Hyuk-Jae
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2012.07a
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    • pp.269-270
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    • 2012
  • Features which exhibit scale and rotation invariance, such as SIFT, are notorious for expensive computation time, and often overlooked for real-time tracking scenarios. This paper proposes a descriptorless matching algorithm based on motion vectors between consecutive frames to find the geometrically closest candidate to each tracked reference feature in the database. Descriptor-less matching forgoes expensive SIFT descriptor extraction without loss of matching accuracy and exhibits dramatic speed-up compared to traditional, naive matching based trackers. Descriptor-less SIFT tracking runs in real-time on an Intel dual core machine at an average of 24 frames per second.

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Matching Algorithm for Hangul Recognition Based on PDA

  • Kim Hyeong-Gyun;Choi Gwang-Mi
    • Journal of information and communication convergence engineering
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    • v.2 no.3
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    • pp.161-166
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    • 2004
  • Electronic Ink is a stored data in the form of the handwritten text or the script without converting it into ASCII by handwritten recognition on the pen-based computers and Personal Digital Assistants(PDA) for supporting natural and convenient data input. One of the most important issue is to search the electronic ink in order to use it. We proposed and implemented a script matching algorithm for the electronic ink. Proposed matching algorithm separated the input stroke into a set of primitive stroke using the curvature of the stroke curve. After determining the type of separated strokes, it produced a stroke feature vector. And then it calculated the distance between the stroke feature vector of input strokes and one of strokes in the database using the dynamic programming technique.

Panoramic Image Stitching using Feature Extracting and Matching on Mobile Device (모바일 기기에서 특징적 추출과 정합을 활용한 파노라마 이미지 스티칭)

  • Lee, Yong-Hwan;Kim, Heung-Jun
    • Journal of the Semiconductor & Display Technology
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    • v.15 no.4
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    • pp.97-102
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    • 2016
  • Image stitching is a process of combining two or more images with overlapping area to create a panorama of input images, which is considered as an active research area in computer vision, especially in the field of augmented reality with 360 degree images. Image stitching techniques can be categorized into two general approaches: direct and feature based techniques. Direct techniques compare all the pixel intensities of the images with each other, while feature based approaches aim to determine a relationship between the images through distinct features extracted from the images. This paper proposes a novel image stitching method based on feature pixels with approximated clustering filter. When the features are extracted from input images, we calculate a meaning of the minutiae, and apply an effective feature extraction algorithm to improve the processing time. With the evaluation of the results, the proposed method is corresponding accurate and effective, compared to the previous approaches.

A Study on the Fingerprint Recognition Method using Neural Networks (신경회로망을 이용한 지문인식방법에 관한 연구)

  • Lee, Ju-Sang;Lee, Jae-Hyeon;Kang, Seong-In;Kim, IL;Lee, Sang-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.11a
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    • pp.287-290
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    • 2000
  • In this paper we have presented approach to automatic the direction feature vectors detection, which detects the ridge line directly in gray scale images. In spite of a greater conceptual complexity, we have shown that our technique has less computational complexity than the complexity of the techniques which require binarization and thinning. Afterwards a various direction feature vectors is changed four direction feature vectors. In this paper used matching method is four direction feature vectors based matching. This four direction feature vectors consist feature patterns in fingerprint images. This feature patterns were used for identification of individuals inputed multilayer Neural Networks(NN) which has capability of excellent pattern identification.

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Stereok Matching based on Intensity and Features for Images with Background Removed (배경을 제외한 영상에서 명암과 특징을 기반으로하는 스테레오 정합)

  • Choe, Tae-Eun;Gwon, Hyeok-Min;Park, Jong-Seung;Han, Jun-Hui
    • Journal of KIISE:Software and Applications
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    • v.26 no.12
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    • pp.1482-1496
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    • 1999
  • 기존의 스테레오 정합 알고리즘은 크게 명암기반기법과 특징기반기법의 두 가지로 나눌 수 있다. 그리고, 각 기법은 그들 나름대로의 장단점을 갖는다. 본 논문은 이 두 기법을 결합하는 새로운 알고리즘을 제안한다. 본 논문에서는 물체모델링을 목적으로 하기 때문에 배경을 제거하여 정합하는 방법을 사용한다. 이를 위해, 정합요소들과 정합유사함수가 정의되고, 정합유사함수는 두 기법사이의 장단점을 하나의 인수에 의해 조절한다. 그 외에도 거리차 지도의 오류를 제거하는 coarse-to-fine기법, 폐색문제를 해결하는 다중윈도우 기법을 사용하였고, 물체의 표면형태를 알아내기 위해 morphological closing 연산자를 이용하여 물체와 배경을 분리하는 방법을 제안하였다. 이러한 기법들을 기반으로 하여 여러가지 영상에 대해 실험을 수행하였으며, 그 결과들은 본 논문이 제안하는 기법의 효율성을 보여준다. 정합의 결과로 만들어지는 거리차 지도는 3차원 모델링을 통해 가상공간상에서 보여지도록 하였다.Abstract Classical stereo matching algorithms can be classified into two major areas; intensity-based and feature-based stereo matching. Each technique has advantages and disadvantages. This paper proposes a new algorithm which merges two main matching techniques. Since the goal of our stereo algorithm is in object modeling, we use images for which background is removed. Primitives and a similarity function are defined. The matching similarity function selectively controls the advantages and disadvantages of intensity-based and feature-based matching by a parameter.As an additional matching strategy, a coarse-to-fine method is used to remove a errorneous data on the disparity map. To handle occlusions, multiple windowing method is used. For finding the surface shape of an object, we propose a method that separates an object and the background by a morphological closing operator. All processes have been implemented and tested with various image pairs. The matching results showed the effectiveness of our method. From the disparity map computed by the matching process, 3D modeling is possible. 3D modeling is manipulated by VRML(Virtual Reality Manipulation Language). The results are summarized in a virtual reality space.

An Object-based Stereo Matching Method Using Block-based Segmentation (블록 기반 영역 분할을 이용한 객체 기반 스테레오 정합 기법)

  • Kwak No-Yoon
    • Journal of Digital Contents Society
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    • v.5 no.4
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    • pp.257-263
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    • 2004
  • This paper is related to the object-based stereo matching algorithm which makes it possible to estimate inner-region disparities for each segmented region. First, several sample points are selected for effectively representing the segmented region, Next, stereo matching is applied to the small area within segmented region which existed in the neighborhood or each sample point. Finally, inner-region disparities are interpolated using a plane equation with disparity of each selected sample. According to the proposed method, the problem of feature-based method that the depth estimation is possible only in the feature points can be solved through the propagation of the disparity in the sample point into the inside of the region. Also, as selecting sample points in contour of segmented region we can effectively suppress obscurity which is occurred in the depth estimation of the monotone region in area-based methods.

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Fingerprint-Based Personal Authentication Using Directional Filter Bank (방향성 필터 뱅크를 이용한 지문 기반 개인 인증)

  • 박철현;오상근;김범수;원종운;송영철;이재준;박길흠
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.4
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    • pp.256-265
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    • 2003
  • To improve reliability and practicality, a fingerprint-based biometric system needs to be robust to rotations of an input fingerprint and the processing speed should be fast. Accordingly, this paper presents a new filterbank-based fingerprint feature extraction and matching method that is robust to diverse rotations and reasonably fast. The proposed method fast extracts fingerprint features using a directional filter bank, which effectively decomposes an image into several subband outputs Since matching is also performed rapidly based on the Euclidean distance between the corresponding feature vectors, the overall processing speed is so fast. To make the system robust to rotations, the proposed method generates a set of feature vectors considering various rotations of an input fingerprint and then matches these feature vectors with the enrolled single template feature vector. Experimental results demonstrated the high speed of the proposed method in feature extraction and matching, along with a comparable verification accuracy to that of other leading techniques.

Another Approach to Stereo Matching - Fuzzification of Feature Values (또다른 접근방식에 의한 스테레오 정합 - 특정 값의 퍼지화)

  • 김동현;최우영;박래홍
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.28B no.11
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    • pp.925-933
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    • 1991
  • Conventional stereo matching techniques are based on the assumption that the features representing an object in left and right images have fixed attribute values. But, in fact, such features may take different values due to the practical stereo image formation and the image acquisition error, and thus the conventional techniques tend to result in the in the incorrect matching of features. In this paper, we propose a stereo matching mathod with a possibilistic view which copes with the possible variability of feature values. As a result, this method decreases the number of incorrect matching features when the values of corresponding features are somewhat large. The effectiveness of the proposed method is shown via computer simulation.

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Content-Based Image Retrieval Algorithm Using HAQ Algorithm and Moment-Based Feature (HAQ 알고리즘과 Moment 기반 특징을 이용한 내용 기반 영상 검색 알고리즘)

  • 김대일;강대성
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.4
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    • pp.113-120
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    • 2004
  • In this paper, we propose an efficient feature extraction and image retrieval algorithm for content-based retrieval method. First, we extract the object using Gaussian edge detector for input image which is key frames of MPEG video and extract the object features that are location feature, distributed dimension feature and invariant moments feature. Next, we extract the characteristic color feature using the proposed HAQ(Histogram Analysis md Quantization) algorithm. Finally, we implement an retrieval of four features in sequence with the proposed matching method for query image which is a shot frame except the key frames of MPEG video. The purpose of this paper is to propose the novel content-based image retrieval algerian which retrieves the key frame in the shot boundary of MPEG video belonging to the scene requested by user. The experimental results show an efficient retrieval for 836 sample images in 10 music videos using the proposed algorithm.