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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...
In this paper, bispectrum-based feature extraction method is proposed for classification of normal vs. pathological infant cries. Bispectrum is a class of higher order spectral analysis, Bispectrum is computed for all segments of normal as well as pathological cries. Bispectrum is a two-dimensional (i.e., 2-D) feature. A tensor is formed using these bispectrum features and then for feature reduction,...
In this paper, we have investigated the effectiveness of Particle swarm optimization (PSO) with extended Kalman smoother (EKS) for fetal ECG extraction from single channel electrocardiogram (ECG) recorded at abdominal area of mother's skin. The abdominal ECG is considered to be composite as it contains both mother's and fetus ECG and is dominated by maternal ECG component. To extract the fetal ECG,...
In this paper, Krawtchouk invariant moments are used as features for object recognition. For hand images, the performance of Krawtchouk moments in terms of recognition accuracy, rotational invariance, scale invariance, computational time and feature vector size, has been analysed. A user independent dataset for 21 subjects under varying illumination conditions is created. A comparative analysis with...
A system is proposed for generation of security key using R-R interval feature of electrocardiogram (ECG) signals as an input. The system provides a mechanism for verification and identification by generating a security key corresponding to an individual. The system comprises of two independent stages: registration and authentication. Biometric security key, created in the registration stage has been...
This paper proposes a fingerprint match algorithm using Minutia Spherical Coordinate Code (MSCC). This algorithm is a modified version of Minutia Cylinder Code (MCC). The advantage of this algorithm is its compact feature representation. Binary vector of every minutia only needs 288 bits, while MCC needs 448 or 1792 bits. This algorithm also uses a greedy alignment approach which can rediscover minutiae...
Automatic matching of poor quality latent fingerprints to rolled/slap fingerprints using an Automated Fingerprint Identification System (AFIS) is still far from satisfactory. Therefore, it is a common practice to have a latent examiner mark features on a latent for improving the hit rate of the AFIS. We propose a synergistic crowd powered latent identification framework where multiple latent examiners...
Sketch recognition is one of the integral components used by law enforcement agencies in solving crime. In recent past, software generated composite sketches are being preferred as they are more consistent and faster to construct than hand drawn sketches. Matching these composite sketches to face photographs is a complex task because the composite sketches are drawn based on the witness description...
Discriminant analysis is an important technique for face recognition because it can extract discriminative features to classify different persons. However, most existing discriminant analysis methods fail to work for single-sample face recognition (SSFR) because there is only a single training sample per person such that the within-class variation of this person cannot be estimated in such scenario...
Despite the high facial expression recognition accuracy reported on individual databases, cross-database facial expression recognition is still a challenging problem. This is essentially a problem of generalizing a facial expression recognizer trained with data of certain subjects under certain conditions to different subjects and/or different conditions. Such generalization capability is crucial...
Security is an important aspect in the practical deployment of biometric authentication systems. Biometric data in its original form is irreplaceable and thus, must be protected. This often comes at the cost of reduced matching accuracy or loss of the true key-less convenience biometric authentication can offer. In this paper, we address the shortcomings of current face template protection schemes...
Biometric recognition has undoubtedly made great strides over the past 50 years. To ensure that current academic research in biometrics has a positive impact on future technological developments, this paper documents some guidelines encouraging researchers to focus on high-impact problems, develop solutions that are practically viable, report results using sound experimental and evaluation protocols,...
Subspace learning is an important technique to enhance the discriminative ability of feature representation and reduce the dimension to improve its efficiency. Due to limited training samples and the usual high-dimensional feature, subspace learning always suffers from overfitting problem, which affects its generalization performance. One possible method is to introduce prior information as a regularizer...
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...
Multispectral iris recognition uses information from multiple bands of the electromagnetic spectrum to better represent certain physiological characteristics of the iris texture and enhance obtained recognition accuracy. This paper addresses the questions of single versus cross-spectral performance and compares score-level fusion accuracy for different feature types, combining different wavelengths...
Dropout rates for students in correspondence and open courses are on increase. There is a need of analysis of factors causing increase in dropout rate. The discovery of hidden knowledge from the educational data system by the effective process of data mining technology to analyze factors affecting student drop out can lead to a better academic planning and management to reduce students drop out from...
This paper presents an attempt to solve the challenging problem of Devanagari numeral and character recognition. It uses structural and geometric features to represent the Devanagari numerals and characters. Each image is zoned in 9 blocks and 8 structural features are extracted from each block. Similarly 9 global geometric features are extracted. These 81 features are used for representing the image...
Newborn swapping, missing, mixing, and illegal adoption is a global challenge and to resolve this emerging issue very less research has been done. Most of the biometric systems are developed for adults and extremely few of them address the difficulty of newborn recognition. As they are the highly non cooperative users of biometrics the ear of newborn may be a perfect source of data for passive identification...
The purpose of the presented research was the development of a melody search system that would allow to find a song in a music database, based on humming the tune of a known song fragment. The melody recognition in the developed system is based on comparing vectors of voice pitch values. The best match of the humming pitch vector against all the recordings in the database is searched. An original...
Speech recognition systems generally use delta and delta-delta (velocity and acceleration) coefficients to characterise the dynamics apparent in frame-based representations of speech. These coefficients can be thought of as the errors of simple predictors. This paper describes the use of error coefficients derived from more advanced (and accurate) forms of prediction and interpolation. Both overall...
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