Recognition Algorithm

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Tatsuo Higuchi - One of the best experts on this subject based on the ideXlab platform.

  • a palmprint Recognition Algorithm using phase only correlation
    IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2008
    Co-Authors: Koichi Ito, Takafumi Aoki, Hiroshi Nakajima, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    This paper presents a palmprint Recognition Algorithm using Phase-Only Correlation (POC). The use of phase components in 2D (two-dimensional) discrete Fourier transforms of palmprint images makes it possible to achieve highly robust image registration and matching. In the proposed Algorithm, POC is used to align scaling, rotation and translation between two palmprint images, and evaluate similarity between them. Experimental evaluation using a palmprint image database clearly demonstrates efficient matching performance of the proposed Algorithm.

  • a fingerprint Recognition Algorithm combining phase based image matching and feature based matching
    Lecture Notes in Computer Science, 2006
    Co-Authors: Ayumi Morita, Hiroshi Nakajima, Takafumi Aoki, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    , This paper proposes an efficient fingerprint Recognition Algorithm combining phase-based image matching and feature-based matching. The use of Fourier phase information of fingerprint images makes possible to achieve robust Recognition for weakly impressed, low-quality fingerprint images. Experimental evaluations using two different types of fingerprint image databases demonstrate efficient Recognition performance of the proposed Algorithm compared with a typical minutiae-based Algorithm and the conventional phase-based Algorithm.

Takafumi Aoki - One of the best experts on this subject based on the ideXlab platform.

  • a palmprint Recognition Algorithm using phase only correlation
    IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2008
    Co-Authors: Koichi Ito, Takafumi Aoki, Hiroshi Nakajima, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    This paper presents a palmprint Recognition Algorithm using Phase-Only Correlation (POC). The use of phase components in 2D (two-dimensional) discrete Fourier transforms of palmprint images makes it possible to achieve highly robust image registration and matching. In the proposed Algorithm, POC is used to align scaling, rotation and translation between two palmprint images, and evaluate similarity between them. Experimental evaluation using a palmprint image database clearly demonstrates efficient matching performance of the proposed Algorithm.

  • ICPR - A practical palmprint Recognition Algorithm using phase information
    2008 19th International Conference on Pattern Recognition, 2008
    Co-Authors: Satoshi Iitsuka, Koichi Ito, Takafumi Aoki
    Abstract:

    This paper proposes a practical palmprint Recognition Algorithm using two-dimensional (2D) phase information. The proposed Algorithm (i) reduces the registered data size by registering quantized phase information and (ii) deals with nonlinear distortion between palmprint images by local block matching. Experimental evaluation using palmprint image databases clearly demonstrates efficient Recognition performance of the proposed Algorithm compared with the conventional palmprint Recognition Algorithms.

  • a fingerprint Recognition Algorithm combining phase based image matching and feature based matching
    Lecture Notes in Computer Science, 2006
    Co-Authors: Ayumi Morita, Hiroshi Nakajima, Takafumi Aoki, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    , This paper proposes an efficient fingerprint Recognition Algorithm combining phase-based image matching and feature-based matching. The use of Fourier phase information of fingerprint images makes possible to achieve robust Recognition for weakly impressed, low-quality fingerprint images. Experimental evaluations using two different types of fingerprint image databases demonstrate efficient Recognition performance of the proposed Algorithm compared with a typical minutiae-based Algorithm and the conventional phase-based Algorithm.

Yuanyuan Jiang - One of the best experts on this subject based on the ideXlab platform.

  • Optimization of Convolutional Neural Network Target Recognition Algorithm
    DEStech Transactions on Computer Science and Engineering, 2018
    Co-Authors: Yuanyuan Jiang
    Abstract:

    This paper proposes an optimized convolutional neural network target Recognition Algorithm for the problem of low Recognition rate of synthetic aperture radar (SAR) target training, under the condition of insufficient tag data, translation, rotation and complexity. In order to overcome the shortage of tag data, the convolutional neural network is initialized with a feature set, obtained by principal component analysis (PCA) unsupervised training. In order to improve the training speed while avoiding overfitting, Rectified Linear Unit (ReLU) function is used as the activation function. In order to enhance robustness and reduce the effect of down sampling on feature representation, this work uses a maximum probability sampling method and normalizes the local contrast of feature after convolution layers. The experimental result shows that, compared with traditional convolutional neural network, this approach achieves a higher Recognition rate for SAR target and better robustness to various image deformation and complex background.

Hiroshi Nakajima - One of the best experts on this subject based on the ideXlab platform.

  • a palmprint Recognition Algorithm using phase only correlation
    IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2008
    Co-Authors: Koichi Ito, Takafumi Aoki, Hiroshi Nakajima, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    This paper presents a palmprint Recognition Algorithm using Phase-Only Correlation (POC). The use of phase components in 2D (two-dimensional) discrete Fourier transforms of palmprint images makes it possible to achieve highly robust image registration and matching. In the proposed Algorithm, POC is used to align scaling, rotation and translation between two palmprint images, and evaluate similarity between them. Experimental evaluation using a palmprint image database clearly demonstrates efficient matching performance of the proposed Algorithm.

  • a fingerprint Recognition Algorithm combining phase based image matching and feature based matching
    Lecture Notes in Computer Science, 2006
    Co-Authors: Ayumi Morita, Hiroshi Nakajima, Takafumi Aoki, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    , This paper proposes an efficient fingerprint Recognition Algorithm combining phase-based image matching and feature-based matching. The use of Fourier phase information of fingerprint images makes possible to achieve robust Recognition for weakly impressed, low-quality fingerprint images. Experimental evaluations using two different types of fingerprint image databases demonstrate efficient Recognition performance of the proposed Algorithm compared with a typical minutiae-based Algorithm and the conventional phase-based Algorithm.

Koji Kobayashi - One of the best experts on this subject based on the ideXlab platform.

  • a palmprint Recognition Algorithm using phase only correlation
    IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2008
    Co-Authors: Koichi Ito, Takafumi Aoki, Hiroshi Nakajima, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    This paper presents a palmprint Recognition Algorithm using Phase-Only Correlation (POC). The use of phase components in 2D (two-dimensional) discrete Fourier transforms of palmprint images makes it possible to achieve highly robust image registration and matching. In the proposed Algorithm, POC is used to align scaling, rotation and translation between two palmprint images, and evaluate similarity between them. Experimental evaluation using a palmprint image database clearly demonstrates efficient matching performance of the proposed Algorithm.

  • a fingerprint Recognition Algorithm combining phase based image matching and feature based matching
    Lecture Notes in Computer Science, 2006
    Co-Authors: Ayumi Morita, Hiroshi Nakajima, Takafumi Aoki, Koji Kobayashi, Tatsuo Higuchi
    Abstract:

    , This paper proposes an efficient fingerprint Recognition Algorithm combining phase-based image matching and feature-based matching. The use of Fourier phase information of fingerprint images makes possible to achieve robust Recognition for weakly impressed, low-quality fingerprint images. Experimental evaluations using two different types of fingerprint image databases demonstrate efficient Recognition performance of the proposed Algorithm compared with a typical minutiae-based Algorithm and the conventional phase-based Algorithm.

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