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This paper presents a simple and fast face recognition system based on two states of discrete Hidden Markov Model (HMM). The minimization in the number of states leads to high processing speed and less memory occupation. Median filter is applied to each image under process, where it is the most suitable filter used to eliminate the effect of noise on images, and thereby enhancing the performance of...
We propose a mandarin Chinese singing voice synthesis system, in which hidden Markov model (HMM)-based speech synthesis technique is used. A mandarin Chinese singing voice corpus is recorded and musical contextual features are well designed for training. F0 and spectrum of singing voice are simultaneously modeled with context-dependent HMMs. There is a new problem, F0 of singing voice is always sparse...
This paper presents a new statistical model for describing real textured images. Our model is based on the observation that the Scale-Invariant Feature Transform (SIFT) descriptors extracted from a given image can be properly modeled by the Gamma distribution. The maximum-likehood algorithm was used to estimate the two parameters of the Gamma distribution. The efficiency of the proposed approach was...
A subspace regularization approach is proposed for eigenfeatures extraction and regularization in human activity recognition. In this approach the within-class subspace is modelled using more eigenvalues from the reliable subspace to obtain a four parameter modelling scheme. This regularization is done in one piece, therefore avoiding undue complexity of modelling eigenspectrum differently. The whole...
Procedural textures have been widely used as they can be easily generated from various mathematical models. However, the model parameters are not perceptually meaningful or uniform for non-expert users; therefore it is difficult for general users to obtain a desired texture by tuning the parameters. In order to satisfy users' requirement, we propose a novel procedural texture retrieval scheme that...
This paper proposes a multimodal human personal recognition system based on palm print and knuckle print. Palm is the inner surface of the hand that extends from the wrist to the base of the fingers and contains a lot of unique pattern of ridges, valleys, principal lines and wrinkles. On the other hand, Knuckle is the part of a finger at a joint where bone is near the surface. Pattern formation at...
This paper presents a novel method for online product recommendation using facial image recognition and emotional feedback for online users. The system detects the faces of the users from the live camera stream along with gender identification and product recommendation algorithms for targeting products to the right user. It also uses an emotion detection technique for getting a feedback about the...
In this paper, we propose a novel feature descriptor for person re-identification without personal information. It is called Water-Drop Render Box (WDRB). The WDRB method is calculated by three steps with target color and its histogram: registration of target color, transformation of distance map, and enhancement of color using target histogram. In order to calculate WDRB, person's top-view images...
In the last years, the electrocardiogram signal has become an important biometric modality due essentially to the physiological or/and behavioral characteristics variation of the heart among different individuals. The aim of this paper is to present a human identification approach using some time and frequency features of the QRS complex of the ECG signal. These features are extracted from a fractional...
Lately, finger vein has been recognized as an efficacious biometric method for user authentication due to the uniqueness of vein patterns and its insusceptibility to forgery because the vein patterns reside inside the human body. In this work, hybrid histogram descriptor is the proposed method. This method utilizes the sign and magnitude components of the texture extracted by using Binary Gradient...
Speaker verification deals with the task of confirming the identity of a claim using a hypothesized speaker model and a speaker model database. This work concentrates on a speaker verification system by combining GMM and SVM. The feature vectors used for modelling are Mel Frequency Cepstral Coefficients (MFCC). The database is collected through different recording equipments which is considered as...
In Speaker Recognition (SR) system, feature extraction is one of the crucial steps where the particular speaker related information are extracted. The state of the art algorithm for this purpose is Mel Frequency Cepstral Coefficient (MFCC), and its complementary feature, Inverted Mel Frequency Cepstral Coefficient (IMFCC). MFCC is based on mel scale and IMFCC is based on inverted mel (imel) scale...
In Speaker Recognition (SR) system, feature extraction is one of the crucial steps where the particular speaker related information is extracted. The state of the art algorithm for this purpose is Mel Frequency Cepstral Coefficient (MFCC), and its complementary feature, Inverted Mel Frequency Cepstral Coefficient (IMFCC). MFCC is based on mel scale and IMFCC is based on inverted mel (imel) scale....
This paper is intended to support the preservation of national cultural asset, particularly for ancient symbols. By using image processing principle, an automatic system that can be designed and implemented to translate ancient manuscript documents. The system is composed of several phases, from scanning, preprocessing, segmentation, feature extraction and classification. Sample images of the document...
The use of directional patterns has recently received more attention in fingerprint classification. It provides a global representation of a fingerprint, by dividing it into homogeneous orientation partitions. With this technique, the challenge in previous works has been the complexity of the pattern templates used for classification. In addition, incomplete fingerprints are often not accounted for...
Driver Assistance Systems such as traffic sign detection and autonomous car research are largely facilitated with the recent advances on computer vision and pattern recognition. In this work, Bag of visual Words technique has been implemented on Speeded Up Robust Feature (SURF) descriptors of the traffic signs and later the sturdy classifier Support Vector Machine (SVM) is used to categorize the traffic...
Minutiae-based vector representation algorithms have been proposed, which allow us not only to speed up matching tasks, but also to easily apply for various template protection techniques, such as Fuzzy Vault, Fuzzy Commitment, and BioHashing. In this paper, we propose a new vectorized fingerprint descriptor called Minutiae Relation Code(MRC), which consists of a set of vector-represented minutiae...
This paper presents some improvements of a rotation invariant method based on AutoRegressive (AR) 2D Models to classify textures. The basic model and our improved version are applied to natural sidescan sonar images (with multiplicative noise) in order to extract a reduced set of relevant rotation invariant features which are then used to feed a MultiLayer Perceptron (MLP) for identification task...
The perception-based approach of feature extraction methods for CBIR has been summarized. It has proposed an experimental analysis of mathematical modeling of textural contents for images, having a perceptual meaning and application such as coarseness, directionality, contrast, and busyness. An objective is to find an effective method to estimate perceptual features. So a cumulative use of computational...
Speech to Speech translation (S2ST) systems are very important for processing by which a spoken utterance in one language is used to produce a spoken output in another language. In S2ST techniques, so far, linguistic information has been mainly adopted without para- and non-linguistic information (emotion, individuality and gender, etc.). Therefore, this systems have a limitation in synthesizing affective...
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