Heikki Kälviäinen

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T. Kauppi1 V. Kalesnykiene2 J.-K. Kamarainen1,3 L. Lensu1 I. Sorri2 A. Raninen2 R. Voutilainen2 J. Pietilä4 H. Kälviäinen1 H. Uusitalo2 1Machine Vision and Pattern Recognition Research Group, Lappeenranta University of Technology 2 Department of Ophthalmology, Faculty of Medicine, University of Kuopio 3 Centre for Vision, Speech and Signal Processing,(More)
Automatic diagnosis of diabetic retinopathy from digital fundus images has been an active research topic in the medical image processing community. The research interest is justified by the excellent potential for new products in the medical industry and significant reductions in health care costs. However, the maturity of proposed algorithms cannot be(More)
For a particularly long time, automatic diagnosis of diabetic retinopathy from digital fundus images has been an active research topic in the medical image processing community. The research interest is justified by the excessive potential for new products in the medical industry and possible reductions in healthcare costs. However, the maturity of(More)
Statistical methods have certain advantages which advocate their use in pattern recognition. One central problem in statistical methods is estimation of class conditional probability density functions based on examples in a training set. In this study maximum likelihood estimation methods for Gaussian mixture models are reviewed and discussed from a(More)
We present a novel method for localizing faces in person identification scenarios. Such scenarios involve high resolution images of frontal faces. The proposed algorithm does not require color, copes well in cluttered backgrounds, and accurately localizes faces including eye centers. An extensive analysis and a performance evaluation on the XM2VTS database(More)
Invariant object recognition is one of the most challenging problems in computer vision. The authors propose a simple Gabor feature space, which has been successfully applied to applications, e.g., in invariant face detection to extract facial features in demanding environments. In the proposed feature space, illumination, rotation, scale, and translation(More)
For almost three decades the use of features based on Gabor filters has been promoted for their useful properties in image processing. The most important properties are related to invariance to illumination, rotation, scale, and translation. These properties are based on the fact that they are all parameters of Gabor filters themselves. This is especially(More)
Rapid computation of the Hough Transform is necessary in very many computer vision applications. One of the major approaches for fast Hough Transform computation is based on the use of a small random sample of the data set rather than the full set. Two diierent algorithms within this family are the Randomized Hough Transform (RHT) and the Probabilistic(More)