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Publications (2)0 Total impact

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    ABSTRACT: Image inpainting is a technique for estimating missing pixel values in an image by using the pixel value information obtained from neighbor pixels of a missing pixel or the prior knowledge derived from learning the object class. In this paper, we propose a fast and accurate image inpainting method using similarity of the subspace. The proposed method generates the subspace from many images related to the object class in the learning step and estimates the missing pixel values of the input image belonging to the same object class so as to maximize the similarity between the input image and the subspace in the inpainting step. Through a set of experiments, we demonstrate that the proposed method exhibits excellent performance in terms of both inpainting accuracy and computation time compared with conventional algorithms.
    18th IEEE International Conference on Image Processing, ICIP 2011, Brussels, Belgium, September 11-14, 2011; 01/2011
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    ABSTRACT: This paper proposes a 2D face recognition algorithm using phase-based correspondence matching. The phase information obtained from 2D DFT (Discrete Fourier Transform) of images contains important information of image representation. The phase-based image matching is successfully applied to sub-pixel image registration tasks for computer vision applications and image recognition tasks for biometric authentication applications. Hierarchical block matching using phase information, i.e, phase-based correspondence matching, can find the corresponding points on the input image from the reference points on the registered image with sub-pixel accuracy. For face recognition, the phase-based correspondence matching is useful for minute change of texture, such as facial expression change, illumination change, etc. Experimental evaluation using the CSU Face Identification Evaluation System with the FERET database demonstrates efficient recognition performance of the proposed algorithm compared with the conventional face recognition algorithms.
    Ninth IEEE International Conference on Automatic Face and Gesture Recognition (FG 2011), Santa Barbara, CA, USA, 21-25 March 2011; 01/2011