Marcos Faundez-Zanuy

On-line signature recognition based on VQ-DTW

This paper studies some pattern recognition algorithms for on-line signature recognition: vector quantization (VQ), nearest neighbor (NN), dynamic time warping (DTW) and hidden Markov models (HMM). We have used a database of 330 users which includes 25 skilled forgeries performed by five different impostors. This database is larger than the typical ones found in the literature. Experimental results reveal that our first proposed combination of VQ and DTW (by means of score fusion) outperforms the other algorithms (DTW, HMM) and achieves a minimum detection cost function (DCF) value equal to 1.37% for random forgeries and 5.42% for skilled forgeries. In addition, we present another combined DTW-VQ scheme which enables improvement of privacy for remote authentication systems, avoiding the submission of the whole original dynamical signature information (using codewords, instead of feature vectors). This system achieves similar performance than DTW.

Data fusion in biometrics

Any biometric system has drawbacks and cannot warranty 100% identification rates, nor 0% false acceptance and rejection ratios. One way to overcome the limitations is through a combination of different biometric systems. In addition, a multimodal biometric recognition is more difficult to fool than a single, biometric system, because it is more unlikely to defeat two or three biometric systems than one. This paper summarizes the different data fusion levels, and how it must be performed in order to improve the results of each combined system on its own

BiosecurID: a multimodal biometric database

A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol. The database includes eight unimodal biometric traits, namely: speech, iris, face (still images, videos of talking faces), handwritten signature and handwritten text (on-line dynamic signals, off-line scanned images), fingerprints (acquired with two different sensors), hand (palmprint, contour-geometry) and keystroking. The database comprises 400 subjects and presents features such as: realistic acquisition scenario, balanced gender and population distributions, availability of information about particular demographic groups (age, gender, handedness), acquisition of replay attacks for speech and keystroking, skilled forgeries for signatures, and compatibility with other existing databases. All these characteristics make it very useful in research and development of unimodal and multimodal biometric systems.

State-of-the-art in speaker recognition

Recent advances in speech technologies have produced new tools that can be used to improve the performance and flexibility of speaker recognition. While there are few degrees of freedom or alternative methods when using fingerprint or iris identification techniques, speech offers much more flexibility and different levels to perform recognition: the system can force the user to speak in a particular manner, different for each attempt to enter. Also, with voice input, the system has other degrees of freedom, such as the use of knowledge/codes that only the user knows, or dialectical/semantical traits that are difficult to forge. This paper offers an overview of the state-of-the-art in speaker recognition, with special emphasis on the pros and cons, and the current research lines. The current research lines include improved classification systems, and the use of high level information by means of probabilistic grammars. In conclusion, speaker recognition is far away from being a technology where all the possibilities have already been explored.

On the vulnerability of biometric security systems

This paper presents an overview of the weakness of biometric security systems and possible solutions to improve it. Different levels of attack are described, and the strengths and weaknesses of the main biometric system are emphasized. Solutions are provided with special emphasis on cryptography and watermarking techniques.

Biometric security technology

This paper presents an overview of the main topics related to biometric security technology, with the central purpose to provide a primer on this subject. Biometrics can offer greater security and convenience than traditional methods for people recognition. Even if we do not want to replace a classic method (password or handheld token) by a biometric one, for sure, we are potential users of these systems, which will even be mandatory for new passport models. For this reason, it is useful to be familiarized with the possibilities of biometric security technology

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

An efficient low cost approach for on-line signature recognition based on length normalization and fractional distances

This work presents a new proposal for an efficient on-line signature recognition system with very low computational load and storage requirements, suitable to be used in resource-limited systems like smart-cards. The novelty of the proposal is in both the feature extraction and classification stages, since it is based on the use of size normalized signatures, which allows for similarity estimation, usually based on dynamic time warping (DTW) or hidden Markov models (HMMs), to be performed by an easy distance calculation between vectors, which is computed using fractional distance, instead of the more typical Euclidean one, so as to overcome the concentration phenomenon that appears when data are high dimensional. Verification and identification tasks have been carried out using the MCYT database, achieving an EER (common threshold) of 6.6% and 1.8% with skilled and random forgeries, respectively, in the first task and 3.6% of error in the second. The proposed system outperforms DTW-based and HMM-based ones, even though these have proved to be very efficient in on-line signature recognition, with storage requirements between 9 and 90 times lesser and a processing speed between 181 and 713 times greater than the DTW-based systems.

Verbal and Nonverbal Communication Behaviours

COST 2102: Cross-Modal Analysis of Verbal and Nonverbal Communication (CAVeNC).- I - Verbal and Noverbal Coding Schema.- Annotation Schemes for Verbal and Non-Verbal Communication: Some General Issues.- Presenting in Style by Virtual Humans.- Analysis of Nonverbal Involvement in Dyadic Interactions.- II - Emotional Expressions.- Childrens Perception of Musical Emotional Expressions.- Emotional Style Conversion in the TTS System with Cepstral Description.- Meaningful Parameters in Emotion Characterisation.- III - Gestural Expressions.- Prosodic and Gestural Expression of Interactional Agreement.- Gesture, Prosody and Lexicon in Task-Oriented Dialogues: Multimedia Corpus Recording and Labelling.- Egyptian Grunts and Transportation Gestures.- IV - Analysis and Algorithms for Verbal and Nonverbal Speech.- On the Use of NonVerbal Speech Sounds in Human Communication.- Speech Spectrum Envelope Modeling.- Using Prosody in Fixed Stress Languages for Improvement of Speech Recognition.- Single-Channel Noise Suppression by Wavelets in Spectral Domain.- Voice Source Change During Fundamental Frequency Variation.- A Gesture-Based Concept for Speech Movement Control in Articulatory Speech Synthesis.- A Novel Psychoacoustically Motivated Multichannel Speech Enhancement System.- Analysis of Verbal and Nonverbal Acoustic Signals with the Dresden UASR System.- V - Machine Multimodal Interaction.- VideoTRAN: A Translation Framework for Audiovisual Face-to-Face Conversations.- Spoken and Multimodal Communication Systems in Mobile Settings.- Multilingual Augmentative Alternative Communication System.- Analysis and Synthesis of Multimodal Verbal and Non-verbal Interaction for Animated Interface Agents.- Generating Nonverbal Signals for a Sensitive Artificial Listener.- Low-Complexity Algorithms for Biometric Recognition.- Towards to Mobile Multimodal Telecommunications Systems and Services.- Embodied Conversational Agents in Wizard-of-Oz and Multimodal Interaction Applications.- Telling Stories with a Synthetic Character: Understanding Inter-modalities Relations.

Signature recognition state-of-the-art

A summarization of one of the most successful behavioral biometric recognition methods: signature recognition. Probably this is one of the oldest biometric recognition methods, with high legal acceptance. Technological advances have made possible new perspectives for signature recognition, by means of capturing devices which provide more than the simple signature image: pressure, acceleration, etc., making it even more difficult to forge a signature.