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Label propagation based on local information with adaptive
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Recognizing the sense of speech is one of the most active research topics in speech processing and in human-computer interaction programs. Despite a wide range of studies in this scope, there is still a long gap among the natural feelings... more
Recognizing the sense of speech is one of the most active research topics in speech processing and in human-computer interaction programs. Despite a wide range of studies in this scope, there is still a long gap among the natural feelings of humans and the perception of the computer. In general, a sensory recognition system from speech can be divided into three main sections: attribute extraction, feature selection, and classification. In this paper, features of fundamental frequency (FEZ) (F0), energy (E), zero-crossing rate (ZCR), fourier parameter (FP), and various combinations of them are extracted from the data vector, Then, the principal component analysis (PCA) algorithm is used to reduce the number of features. To evaluate the system performance. The fusion of each emotional state will be performed later using support vector machine (SVM), K-nearest neighbor (KNN), In terms of comparison, similar experiments have been performed on the emotional speech of the German language,...
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Abstract Finding the interrelationship between EEG time series at both sensory and source levels during a mental task is helpful in understanding the corresponding neural functionality. Based on such connectivity measures, a functional... more
Abstract Finding the interrelationship between EEG time series at both sensory and source levels during a mental task is helpful in understanding the corresponding neural functionality. Based on such connectivity measures, a functional brain connectivity network can be formed, which shows the relationship and the extent of dependency among the aforementioned time series. In order to evaluate the interdependency of EEG signals acquired from different electrodes, we proposed a new nonlinear connectivity index based on correntropy spectral density. Here, the correntropy function was defined as a sum of weighted positive definite kernels. Optimal weights were found by solving a quadratic optimization problem. In order to evaluate the proposed approach for determining the interrelationships, Henon map, two synthetically related simulated signals, and EEG signals (BCI competition IV data) were employed. The suggested coherence measure shows robustness to noise and high sensitivity to sudden changes in coupling strength. This measure is able to detect nonlinear as well as linear coupling of EEG signals. In general, the proposed method is more efficient than other methods like coherence and partial coherence method, is capable of showing the similarity between the two signals, and preserves the frequency characteristics of the system.
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With the increasing demand for image-based applications, the efficient and reliable evaluation of image quality has increased in importance. Measuring the image quality is of fundamental importance for numerous image processing... more
With the increasing demand for image-based applications, the efficient and reliable evaluation of image quality has increased in importance. Measuring the image quality is of fundamental importance for numerous image processing applications, where the goal of image quality assessment (IQA) methods is to automatically evaluate the quality of images in agreement with human quality judgments. Numerous IQA methods have been proposed over the past years to fulfill this goal. In this paper, a survey of the quality assessment methods for conventional image signals, as well as the newly emerged ones, which includes the high dynamic range (HDR) and 3-D images, is presented. A comprehensive explanation of the subjective and objective IQA and their classification is provided. Six widely used subjective quality datasets, and performance measures are reviewed. Emphasis is given to the full-reference image quality assessment (FR-IQA) methods, and 9 often-used quality measures (including mean squared error (MSE), structural similarity index (SSIM), multi-scale structural similarity index (MS-SSIM), visual information fidelity (VIF), most apparent distortion (MAD), feature similarity measure (FSIM), feature similarity measure for color images (FSIMC), dynamic range independent measure (DRIM), and tone-mapped images quality index (TMQI)) are carefully described, and their performance and computation time on four subjective quality datasets are evaluated. Furthermore, a brief introduction to 3-D IQA is provided and the issues related to this area of research are reviewed.
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In this paper, we address the discrimination of mental tasks problem and suggest a method based on Ensemble Empirical Mode Decomposition (EEMD), for time-frequency analysis, and a pattern selection method based on an information theoretic... more
In this paper, we address the discrimination of mental tasks problem and suggest a method based on Ensemble Empirical Mode Decomposition (EEMD), for time-frequency analysis, and a pattern selection method based on an information theoretic measure, namely; Jensen Shannon Divergence (JSD) measure. The method works in three steps: (i) to employ EEMD for EEG signal decomposition into components called Intrinsic Mode Functions (IMFs), followed by applying Hilbert transform to the IMFs to determine the instantaneous frequency and amplitude; (ii) to choose the IMFs containing the most significant information based on the degree of presence in gamma band; (iii) to select segments of instantaneous vectors according to JSD metric, which measures the distances between two concepts. This method was applied to EEG signals of 5 subjects performing 5 mental tasks. The classification of mental tasks was performed using Fisher linear discriminator. The experimental results are compared with the ones obtained by a method that uses the power of gamma band in EEG signals (a traditional and popular method). The experimental results show improvement of the classification accuracy.
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Eye tracking and gaze-point estimation has increasing applications in the field of human-machine interface. Although so far a number of gaze-point estimation algorithms were investigated by researchers, video-based methods can be counted... more
Eye tracking and gaze-point estimation has increasing applications in the field of human-machine interface. Although so far a number of gaze-point estimation algorithms were investigated by researchers, video-based methods can be counted as the most important and efficient category in which eye features are obtained by processing of eye images. One of the most important factors affecting on the accuracy of gaze-point estimation is high-accurate extraction of pupil boundary. In this paper, a new method based on active contours is proposed for pupil boundary extraction. Active contours are among the conventional and useful methods for image segmentation. Generally, deformable models are curves that can evolve in order to minimize the internal and external energies in image domain. The internal energy keeps the curve smooth and differentiable, while the external energy directs the curve to the desired properties. Experimental results demonstrated suitable performance of the proposed me...
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With the increasing demand for image-based applications, the efficient and reliable evaluation of image quality has increased in importance. Measuring the image quality is of fundamental importance for numerous image processing... more
With the increasing demand for image-based applications, the efficient and reliable evaluation of image quality has increased in importance. Measuring the image quality is of fundamental importance for numerous image processing applications, where the goal of image quality assessment (IQA) methods is to automatically evaluate the quality of images in agreement with human quality judgments. Numerous IQA methods have been proposed over the past years to fulfill this goal. In this paper, a survey of the quality assessment methods for conventional image signals, as well as the newly emerged ones, which includes the high dynamic range (HDR) and 3-D images, is presented. A comprehensive explanation of the subjective and objective IQA and their classification is provided. Six widely used subjective quality datasets, and performance measures are reviewed. Emphasis is given to the full-reference image quality assessment (FR-IQA) methods, and 9 often-used quality measures (including mean squa...
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— A progressive and scalable, region of interest (ROI) image coding scheme based on matching pursuits (MP) is presented. Matching pursuit is a multi-resolutional signal analysis tool and can be employed in order to progressively refine... more
— A progressive and scalable, region of interest (ROI) image coding scheme based on matching pursuits (MP) is presented. Matching pursuit is a multi-resolutional signal analysis tool and can be employed in order to progressively refine the quality of a set of selected regions of an image up to a specific grade. The computational complexity of this analysis method can be reduced by decreasing the size of MP dictionary. Thus, the proposed method provides a trade off between complexity, rate, and quality. By the suggested scheme, regions of an image with higher receiver’s priority are refined in an interactive manner. The transmitter sends an initial coarse version of the image. Then, he receiver transmits its preferred ROI parameters. Afterwards, the reconstructed image is refined according to the ROI parameters, in a progressive way. I.
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Recognizing the sense of speech is one of the most active research topics in speech processing and in human-computer interaction programs. Despite a wide range of studies in this scope, there is still a long gap among the natural feelings... more
Recognizing the sense of speech is one of the most active research topics in speech processing and in human-computer interaction programs. Despite a wide range of studies in this scope, there is still a long gap among the natural feelings of humans and the perception of the computer. In general, a sensory recognition system from speech can be divided into three main sections: attribute extraction, feature selection, and classification. In this paper, features of fundamental frequency (FEZ) (F0), energy (E), zero-crossing rate (ZCR), fourier parameter (FP), and various combinations of them are extracted from the data vector, Then, the principal component analysis (PCA) algorithm is used to reduce the number of features. To evaluate the system performance. The fusion of each emotional state will be performed later using support vector machine (SVM), K-nearest neighbor (KNN), In terms of comparison, similar experiments have been performed on the emotional speech of the German language,...
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AbstractWe have developed novel progressive scalable re-gion-of-interest (ROI) image compression schemes with rate-dis-tortion-complexity tradeoff based on vector quantization. Residual vector quantization (RVQ) equips the encoder with a... more
AbstractWe have developed novel progressive scalable re-gion-of-interest (ROI) image compression schemes with rate-dis-tortion-complexity tradeoff based on vector quantization. Residual vector quantization (RVQ) equips the encoder with a multi-resolu-tion apparatus which is useful ...
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In this paper we pmpose novel pmgressive scalable region of in-term (RO/) image compression schemes wirh mre, disroriion, and complexity rrade-off based on vector quanrizarion. The pmposed schemes are unbalanced in the sense rhar the... more
In this paper we pmpose novel pmgressive scalable region of in-term (RO/) image compression schemes wirh mre, disroriion, and complexity rrade-off based on vector quanrizarion. The pmposed schemes are unbalanced in the sense rhar the decoder har less compurarional ...
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Summary form only given. The perceptual resolution of vision is greatly space variant and is highest at the point of fixation and decreases rapidly away from this point. Novel unstructured and structured vector quantization (VQ) schemes... more
Summary form only given. The perceptual resolution of vision is greatly space variant and is highest at the point of fixation and decreases rapidly away from this point. Novel unstructured and structured vector quantization (VQ) schemes are proposed to take advantage of this ...
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In this thesis, novel progressive scalable region-of-interest (ROI) image coding schemes with rate-distortion-complexity trade-off based on residual vector quantization (RVQ) and matching pursuit (MP) are developed. RVQ and MP provide the... more
In this thesis, novel progressive scalable region-of-interest (ROI) image coding schemes with rate-distortion-complexity trade-off based on residual vector quantization (RVQ) and matching pursuit (MP) are developed. RVQ and MP provide the encoder with multi-resolution signal ...
AbstractJoint source/channel (JSC) decoding based on using the residual redundancy in a source coder output stream is an interesting bandwidth efficient method of reducing the effects of a noisy channel. In this paper, we consider the... more
AbstractJoint source/channel (JSC) decoding based on using the residual redundancy in a source coder output stream is an interesting bandwidth efficient method of reducing the effects of a noisy channel. In this paper, we consider the problem of JSC decoding of a matching ...