Huseyin Ozkaramanli

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The condition on scaling filters of two orthogonal wavelet bases that render the corresponding wavelets as Hilbert transform pairs is re-examined in this note. Without making any pre-assumption on the relationship between the two scaling filters, the authors derive necessary and sufficient conditions for forming Hilbert transform pairs. They lead to new(More)
Facial feature extraction is a fundamental problem in image processing. Correct extraction of features is essential for the success of many applications. Typical feature extraction algorithms fail for low resolution images which do not contain sufficient facial detail. In this paper, a region-based super-resolution aided facial feature extraction method for(More)
Automated visual surveillance systems mostly depend on an effective background subtraction technique. Most background subtraction techniques suffer mainly from parameter updates for threshold selection. A new threshold selection technique, which is found while training the system to learn the background, is proposed.
This paper introduces a face recognition method based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is used to extract features from face images. DT-CWT uses similar kernels with Gabor wavelets and is a computationally cheaper way of extracting Gabor-like features. Principal Component Analysis (PCA) which is a linear dimensionality reduction(More)
Based on a combination of color segmentation, connected components labeling and morphology, an algorithm for human face tracking and facial feature based head tilt angle extraction is developed. The method uses the HSI space for color segmentation, since, in this space, the dynamic range of skin color is quite narrow, thus enabling the differentiation of(More)
This paper proposes an extension to the algorithm of single-image super-resolution based on selective sparse representation over a set of coupled low and high resolution dictionary pairs. The extended algorithm reserves the sparse representation framework for patches of high sharpness values while bicubic interpolation is used to super-resolve un-sharp(More)
In this paper a new system for recognizing faces from video sequences using weighted majority voting (WMV) method is proposed. In the training phase, the system uses principle component analysis (PCA) based single eigenspace generated by sequences of faces of all subjects with the same resolution. For the testing phase, the system employs several(More)
This paper presents a new strategy for directionally-structured dictionary learning and component-wise sparse representation. The signal space is divided into directional subspace triplets. Directionally-selective projection operators are designed for this purpose. Each triplet contains two orthogonal subspaces along with a remainder one. For each triplet,(More)
Based on a combination of color segmentation, connected component labeling and morphology, an algorithm for human face tracking and principal component analysis (PCA) based head tilt angle calculation method is developed. The method uses HSV space for color segmentation since in this space the dynamic range of the skin color is quite narrow thus enabling us(More)
Most digital cameras acquire image information as an incomplete down-sampled representation of the three basic color components, such that one color value is sampled per pixel location. Image demosaicing is the process of retrieving the missing two color components in each pixel. Demosaicing by alternating projections (AP) is one of the most successful(More)
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