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This paper presents a novel method to recognize subtle emotions based on optical strain magnitude feature extraction from the temporal point of view. The common way that subtle emotions are exhibited by a person is in the form of visually observed micro-expressions, which usually occur only over a brief period of time. Optical strain allows small deformations on the face to be computed between successive...
In this paper a simple method is proposed using zero frequency filtering (ZFF) of a close approximate glottal flow derivative (GFD) to extract glottal closure (GCI's) and opening instants (GOI's) from speech. The GFD is obtained from iterative adaptive inverse filtering (IAIF) which contains such instants. It is observed that GCI's can be located by positive zero crossings of zero frequency filtered...
Segmentation is considered as a core step for any recognition or classification method and for the text within any document to be effectively recognized it must be segmented accurately. In this paper a text and writer independent algorithm for the segmentation of sub-words in Arabic words has been presented. The concept is based around the global binarization of an image at various thresholding levels...
In this paper, we present the ATM (Awesome Translation Machine), which translates handwriting texts in English into Chinese, and then provides its pronunciations in both the two languages. Specifically, two types of the databases that contain characters and sentences for training the ATM are constructed. Various signal processing techniques are employed sequentially for processing and analyzing the...
In this paper, we represent a new method for robust speech recognition technique. Speech recognition is a process by which system is able to understand natural language. By the help of proposed method we will be able to give computer system the voice command to perform task. The first step is to take a single audio as an input. The second step is to eliminate the presence of noise. The third step...
Since the past several years, face recognition from video has received significant attention due to wide range of commercial and law enforcement applications, such as surveillance systems, closed circuit TV (CCTV) monitoring, etc. Human face detection is the first and important task in a dynamic environment, such as video, where noise conditions, illuminations, locations of subjects and pose can vary...
In era of information age, due to different electronic, information & communication technology devices and process like sensors, cloud, individual archives, social networks, internet activities and enterprise data are growing exponentially. The most challenging issues are how to effectively manage these large and different type of data. Big data is one of the term named for this large and...
In this paper, new combination of filters was proposed for infant based on Classification of Pain Expressions (COPE) database. Different performance parameters such as Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Image Enhancement Factor (IEF) and Mean Structural SIMilarity (MSSIM) Index ere employed. The results show improved performance of the proposed algorithm in terms of these...
Recently there has been renewed interest in the application of photoplethysmography signals for cardiovascular disease assessment. Photoplethysmography signals are acquired non-invasively using visible and infrared light passed through the finger pulp. Unfortunately, this method commonly suffers from many forms of interference and distortion such as; baseline wander, mains-line interference and random...
Original sequential pattern mining model only considers occurrence frequentness of sequential patterns, disregards their occurrence periodicity. We propose the asynchronous periodic sequential pattern mining model to discover the sequential patterns which are not only occurring frequently, but also appearing periodically. For this mining model, we propose a pattern-growth mining algorithm to mine...
Detection of emotion in humans from speech signals is a recent research field. One of the scenarios where this field has been applied is in situations where the human integrity and security are at risk. In this paper we are propossing a set of features based on the Teager energy operator, and several entropy measures obtained from the decomposition signals from discrete wavelet transform to characterize...
This paper presents a novel method for ECG baseline drift removal while preserving the integrity of the ST segment. Baseline estimation is achieved by tracking 3 isoelectric points within the ECG waveform as fiducial markers used in an interpolation filter. These points are determined relative to the QRS complex, which is extracted using a known method (Pan-Tompkins algorithm). The proposed algorithm...
Pk-anonymization is a data anonymization method that employs randomization. Pk-anonymization guarantees Pk-anonymity, which is an extension of probabilistic k-anonymity. To implement this method, we assign random noise to records to reduce the probability of identifying record owners to less than 1/k. Existing methods assign noise using a Laplace distribution, and determine the variance of the Laplace...
We propose a hierarchical regression approach, Dirichlet-tree cascaded Hough forests (DCHF), which is based on deep learning for continuous head pose estimation in unconstrained environment, e.g., poses, illumination, occlusion, low image resolution, expressions and make-up. First, positive facial patches are learned and extracted from facial area to eliminate the influence of noise. Then, in order...
We propose in this paper a novel example-based method for Gaussian denoising of CT images. In the proposed method, denoising is performed with the help of a set of example CT images. We construct, from the example images, a database consisting of high and low-frequency patch pairs and then use the Markov random field to denoise. The proposed denoising method can restore the high-frequency band that...
Although numerous steganalyzers for least significant bit (LSB) matching have been presented, the detection for uncompressed images and low embedding rates remains challenge for steganalysts. In this paper, we propose a novel method for detection of LSB matching steganography, which is based on the features extracted from a conditional probability matrix described by Markov Mesh Models (MMMs). The...
A novel method for liveness detection of dorsal hand vein (DHV) based on AR model is proposed. Firstly, existing real DHV images are used to constitute a projection space based on modified principal component analysis (PCA). Unlike the previous works using the method of PCA, zero eigenvalues with their eigenvectors are used to constitute the projection space in this work. Secondly, test samples, including...
In this contribution, we study the characteristics of sound generated by wind and a signal model for the synthesis of wind noise signals is derived. An analysis of the statistics of wind noise recorded in a laboratory setup is carried out with respect to the spectral and temporal properties of the signals. In particular, an autoregresive model is developed for the spectral shape description and the...
Iris recognition becomes an important technology in our society. Visual patterns of human iris provide rich texture information for personal identification. However, it is greatly challenging to match intra-class iris images with large variations in unconstrained environments because of noises, illumination variation, heterogeneity and so on. To track current state-of-the-art algorithms in iris recognition,...
Non-intrusive speech intelligibility metrics are based solely on the corrupted speech information and a prior model of the speech signal in a given representation. As such, any sources of variability not taken into account by the model will affect the metric's per-formance. In this paper, we investigate two sources of variability in the auditory-inspired model used by the speech-to-reverberation modulation...
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