• Title/Summary/Keyword: SIFT algorithm

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Novel Parallel Approach for SIFT Algorithm Implementation

  • Le, Tran Su;Lee, Jong-Soo
    • Journal of information and communication convergence engineering
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    • v.11 no.4
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    • pp.298-306
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    • 2013
  • The scale invariant feature transform (SIFT) is an effective algorithm used in object recognition, panorama stitching, and image matching. However, due to its complexity, real-time processing is difficult to achieve with current software approaches. The increasing availability of parallel computers makes parallelizing these tasks an attractive approach. This paper proposes a novel parallel approach for SIFT algorithm implementation using a block filtering technique in a Gaussian convolution process on the SIMD Pixel Processor. This implementation fully exposes the available parallelism of the SIFT algorithm process and exploits the processing and input/output capabilities of the processor, which results in a system that can perform real-time image and video compression. We apply this implementation to images and measure the effectiveness of such an approach. Experimental simulation results indicate that the proposed method is capable of real-time applications, and the result of our parallel approach is outstanding in terms of the processing performance.

Affine Local Descriptors for Viewpoint Invariant Face Recognition

  • Gao, Yongbin;Lee, Hyo Jong
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.781-784
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    • 2014
  • Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we use Affine SIFT to detect affine invariant local descriptors for face recognition under large viewpoint change. Affine SIFT is an extension of SIFT algorithm. SIFT algorithm is scale and rotation invariant, which is powerful for small viewpoint changes in face recognition, but it fails when large viewpoint change exists. In our scheme, Affine SIFT is used for both gallery face and probe face, which generates a series of different viewpoints using affine transformation. Therefore, Affine SIFT allows viewpoint difference between gallery face and probe face. Experiment results show our framework achieves better recognition accuracy than SIFT algorithm on FERET database.

Touch Recognition based on SIFT Algorithm (SIFT 알고리즘 기반 터치인식)

  • Jung, Sung Hoon
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.11
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    • pp.69-75
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    • 2013
  • This paper introduces a touch recognition method for touch screen systems based on the SIFT(Scale Invariant Feature Transform) algorithm for stable touch recognition under strong noises. This method provides strong robustness against the noises and makes it possible to effectively extract the various size of touches due to the SIFT algorithm. In order to verify our algorithm we simulate it on the Matlab with the channel data obtained from a real touch screen. It was found from the simulations that our method could stably recognize the touches without regard to the size and direction of the touches. But, our algorithm implemented on a real touch screen system does not support the realtime feature because the DoG(Difference of Gaussian) of the SIFT algorithm needs too many computations. We solved the problem using the DoM(Difference of Mean) which is a fast approximation method of DoG.

Localization and Autonomous Navigation Using GPU-based SIFT and Virtual Force for Mobile Robots (GPU 기반 SIFT 방법과 가상의 힘을 이용한 이동 로봇의 위치 인식 및 자율 주행 제어)

  • Tak, Myung Hwan;Joo, Young Hoon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.10
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    • pp.1738-1745
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    • 2016
  • In this paper, we present localization and autonomous navigation method using GPU(Graphics Processing Unit)-based SIFT(Scale-Invariant Feature Transform) algorithm and virtual force method for mobile robots. To do this, at first, we propose the localization method to recognize the landmark using the GPU-based SIFT algorithm and to update the position using extended Kalman filter. And then, we propose the A-star algorithm for path planning and the virtual force method for autonomous navigation of the mobile robot. Finally, we demonstrate the effectiveness and applicability of the proposed method through some experiments using the mobile robot with OPRoS(Open Platform for Robotic Services).

A Fast SIFT Implementation Based on Integer Gaussian and Reconfigurable Processor

  • Su, Le Tran;Lee, Jong Soo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.2 no.3
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    • pp.39-52
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    • 2009
  • Scale Invariant Feature Transform (SIFT) is an effective algorithm in object recognition, panorama stitching, and image matching, however, due to its complexity, real time processing is difficult to achieve with software approaches. This paper proposes using a reconfigurable hardware processor with integer half kernel. The integer half kernel Gaussian reduces the Gaussian pyramid complexity in about half [] and the reconfigurable processor carries out a parallel implementation of a full search Fast SIFT algorithm. We use a low memory, fine grain single instruction stream multiple data stream (SIMD) pixel processor that is currently being developed. This implementation fully exposes the available parallelism of the SIFT algorithm process and exploits the processing and I/O capabilities of the processor which results in a system that can perform real time image and video compression. We apply this novel implementation to images and measure the effectiveness. Experimental simulation results indicate that the proposed implementation is capable of real time applications.

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Parallel Implementation and Performance Evaluation of the SIFT Algorithm Using a Many-Core Processor (매니코어 프로세서를 이용한 SIFT 알고리즘 병렬구현 및 성능분석)

  • Kim, Jae-Young;Son, Dong-Koo;Kim, Jong-Myon;Jun, Heesung
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.9
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    • pp.1-10
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    • 2013
  • In this paper, we implement the SIFT(Scale-Invariant Feature Transform) algorithm for feature point extraction using a many-core processor, and analyze the performance, area efficiency, and system area efficiency of the many-core processor. In addition, we demonstrate the potential of the proposed many-core processor by comparing the performance of the many-core processor with that of high-performance CPU and GPU(Graphics Processing Unit). Experimental results indicate that the accuracy result of the SIFT algorithm using the many-core processor was same as that of OpenCV. In addition, the many-core processor outperforms CPU and GPU in terms of execution time. Moreover, this paper proposed an optimal model of the SIFT algorithm on the many-core processor by analyzing energy efficiency and area efficiency for different octave sizes.

Affine Invariant Local Descriptors for Face Recognition (얼굴인식을 위한 어파인 불변 지역 서술자)

  • Gao, Yongbin;Lee, Hyo Jong
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.9
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    • pp.375-380
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    • 2014
  • Under controlled environment, such as fixed viewpoints or consistent illumination, the performance of face recognition is usually high enough to be acceptable nowadays. Face recognition is, however, a still challenging task in real world. SIFT(Scale Invariant Feature Transformation) algorithm is scale and rotation invariant, which is powerful only in the case of small viewpoint changes. However, it often fails when viewpoint of faces changes in wide range. In this paper, we use Affine SIFT (Scale Invariant Feature Transformation; ASIFT) to detect affine invariant local descriptors for face recognition under wide viewpoint changes. The ASIFT is an extension of SIFT algorithm to solve this weakness. In our scheme, ASIFT is applied only to gallery face, while SIFT algorithm is applied to probe face. ASIFT generates a series of different viewpoints using affine transformation. Therefore, the ASIFT allows viewpoint differences between gallery face and probe face. Experiment results showed our framework achieved higher recognition accuracy than the original SIFT algorithm on FERET database.

3D Object Recognition Using Appearance Model Space of Feature Point (특징점 Appearance Model Space를 이용한 3차원 물체 인식)

  • Joo, Seong Moon;Lee, Chil Woo
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.2
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    • pp.93-100
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    • 2014
  • 3D object recognition using only 2D images is a difficult work because each images are generated different to according to the view direction of cameras. Because SIFT algorithm defines the local features of the projected images, recognition result is particularly limited in case of input images with strong perspective transformation. In this paper, we propose the object recognition method that improves SIFT algorithm by using several sequential images captured from rotating 3D object around a rotation axis. We use the geometric relationship between adjacent images and merge several images into a generated feature space during recognizing object. To clarify effectiveness of the proposed algorithm, we keep constantly the camera position and illumination conditions. This method can recognize the appearance of 3D objects that previous approach can not recognize with usually SIFT algorithm.

Patent Document Similarity Based on Image Analysis Using the SIFT-Algorithm and OCR-Text

  • Park, Jeong Beom;Mandl, Thomas;Kim, Do Wan
    • International Journal of Contents
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    • v.13 no.4
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    • pp.70-79
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    • 2017
  • Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.

Mixed Mobile Education System using SIFT Algorithm (SIFT 알고리즘을 이용한 혼합형 모바일 교육 시스템)

  • Hong, Kwang-Jin;Jung, Kee-Chul;Han, Eun-Jung;Yang, Jong-Yeol
    • Journal of the Korea Industrial Information Systems Research
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    • v.13 no.2
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    • pp.69-79
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    • 2008
  • Due to popularization of the wireless Internet and mobile devices the infrastructure of the ubiquitous environment, where users can get information whatever they want anytime and anywhere, is created. Therefore, a variety of fields including the education studies methods for efficiency of information transmission using on-line and off-line contents. In this paper, we propose the Mixed Mobile Education system(MME) that improves educational efficiency using on-line and off-line contents on mobile devices. Because it is hard to input new data and cannot use similar off-line contents in systems used additional tags, the proposed system does not use additional tags but recognizes of-line contents as we extract feature points in the input image using the mobile camera. We use the Scale Invariant Feature Transform(SIFT) algorithm to extract feature points which are not affected by noise, color distortion, size and rotation in the input image captured by the low resolution camera. And we use the client-server architecture for solving the limited storage size of the mobile devices and for easily registration and modification of data. Experimental results show that compared with previous work, the proposed system has some advantages and disadvantages and that the proposed system has good efficiency on various environments.

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