speech emotion recognition (ser) is a new and challenging research area with a wide range of applications in man-machine interactions. the aim of a ser system is to recognize human emotion by analyzing the acoustics of speech sound. in this study, we propose spectral pattern features (sps) and harmonic energy features (hes) for emotion recognition. these features extracted from the spectrogram ...

UNLABELLED The aim of this paper is to propose a partitioned-image filtering technique that is a new way of reducing the Gibbs phenomenon in filtered images. METHODS This technique relies on exploiting the properties of the Gibbs phenomenon and on assumptions about the structure of the image. The amplitude of the Gibbs ringing is directly proportional to the height of the image discontinuity....

We propose dual-domain filtering, an image processing paradigm that couples spatial domain with frequency domain filtering. Our dual-domain defined filter removes artifacts like residual noise of other image denoising methods and compression artifacts. Moreover, iterating the filter achieves state-of-the-art image denoising results, but with a much simpler algorithm than competing approaches. T...

The basic idea behind this work is in extraction (estimation) of the uncorrupted image from the distorted or noised one. The idea is also referred to as the image denoising. Noise removal or noise reduction in an image can be done by linear or nonlinear filtering. The most popular linear technique is based on averaging (or meaning) linear operators. Usually, denoising via linear filters does no...

In this paper, we develop a multilayered genetic based fuzzy image filter, which consists of fuzzy number construction process, a fuzzy filtering process, a genetic learning process and an image knowledge base. The introduction of multilayered fuzzy systems substantially decreases the no of rules to be learnt. First, the fuzzy number construction process receives noise free image and sample ima...

A new inverse halftoning algorithm based on reversible data hiding techniques for halftone images is proposed in this paper. The proposed scheme has the advantages of two commonly used methods, the lookup table (LUT) and Gaussian filtering methods. We embed a part of important LUT templates into a halftone image and restore the lossless image after these templates have been extracted. Then a hy...

in many computer vision applications, segmenting and extraction of moving objects in video sequences is an essential task. background subtraction, by which each input image is subtracted from the reference image, has often been used for this purpose. in this paper, we offer a novel background-subtraction technique for real-time dynamic background generation using color images that are taken fro...

In this work a new version of block-matching and 3D filtering (BM3D) denoising approach introduced by Dabov et al. for denoising the image corrupted by additive white Gassian noise is proposed. The BM3D performs collaborative filtering to the 3D image groups composed by similar image blocks with the fixed hard-thresholding operator. The proposed version of BM3D adopts adaptive block-matching th...

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and t...

We propose a family of methods for biomedical image time series registration based on Particle filtering. The first method applies an intensity-based information-theoretic approach to calculate importance weights. An effective second group of methods use landmark-based approaches for the same purpose by automatically detecting intensity maxima or SIFT interest points from image time series. A b...