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Dive into the research topics where Mihaela Luca is active.

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Featured researches published by Mihaela Luca.


international conference on system theory, control and computing | 2014

PDE-based image restoration using variational denoising and inpainting models

Tudor Barbu; Adrian Ciobanu; Mihaela Luca

A PDE-based image restoration model is proposed in this paper. It aims to restore degraded images that are affected by both noise and missing zones. The considered restoration approach is based on two PDE variational techniques. The first variational method performs an efficient noise reduction, while the second variational model provides the image reconstruction. By using both variational models, one achieves a much better enhancement of the degraded image.


e health and bioengineering conference | 2013

Iris classification using WinICC and LAB color features

Ioan Pavaloi; Adrian Ciobanu; Mihaela Luca

We present the WinICC software package, designed to help in tasks like clusterization or classification of images based on different feature vectors. The capabilities of this software are proven on a classification test involving 1.205 already segmented iris images belonging to 241 persons (five iris images per person - part of the UBIRISv1 Internet available database). We used the k-NN feature of the WinICC applied on LAB color feature vectors with 80 components extracted from iris images. The resulted rates of correctly classified irises are over 88% if 3 or 4 images are used to classify the remaining images of the same person. As the data set is not perfect, this is a result that may suggest a possible identification of human irises based on color distribution.


e health and bioengineering conference | 2013

Iris features using Dual Tree Complex Wavelet Transform in texture evaluation for biometrical identification

Anca Ignat; Mihaela Luca; Adrian Ciobanu

Iris characteristics are accurate and reliable for person identification. We used a new method to extract combined features for color and texture characterization using Dual Tree Complex Wavelet Transform. We applied this feature vectors selection on the UPOL iris color image database. The identification of the subsequent images of the same iris was obtained with competitive results.


Development and Application Systems (DAS), 2014 International Conference on | 2014

Automatic fury recognition in audio records

Adrian Ciobanu; Mihaela Luca; Elena Musca; Ioan Pavaloi

The paper is focused on automatic detection of fury emotion in audio records, using data extracted from the vocalic analysis of formants. We have studied speech prosody and voice inflexions and we recognised fury using classification algorithms applied to two databases, one with professional voices and another with normal voices, both of them recorded on the base of selected texts in Romanian language. We used relevant stories for generating fury emotion. We obtained interesting results that can be used in a large variety of possible applications.


Development and Application Systems (DAS), 2014 International Conference on | 2014

Color feature vectors based on optimal LAB histogram bins

Adrian Ciobanu; Ioan Pavaloi; Mihaela Luca; Elena Musca

In this paper we propose an automatic method for computing the bin boundaries of complex 3D LAB histograms in order to extract optimal color feature vectors from digital images. The size of the feature vectors can be adapted to particular application needs. We tested our approach with very good results on an iris recognition problem solved empirically before.


international conference on system theory, control and computing | 2014

A study on automatic recognition of positive and negative emotions in speech

Ioan Pavaloi; Adrian Ciobanu; Mihaela Luca; E. Musca; Tudor Barbu; Anca Ignat

The paper is focused on an experimental study on positive and negative emotion vocal recognition. After some considerations about the positive and negative emotions, the paper gives a short description of the three corpuses used in the work we have accomplished. The paper describes three sets of coefficients used, the statistic features used to generate the three sets of feature vectors and the two classification methods used in this study. The recognition results obtained for every corpus are shown and some conclusions and directions of development are presented.


soft computing | 2016

Retinal Vessel Classification Technique

Florin Rotaru; Silviu-Ioan Bejinariu; Cristina Diana Niţă; Ramona Luca; Mihaela Luca; Adrian Ciobanu

A retinal vessel classification procedure is proposed. From the image of thinned vessel network, landmarks are extracted and classified as branching, crossover and end points. Then a vascular graph is generated. Using a stratified graph edge labeling procedure the artery/vein map is built. In a first step the graph branches near the optic disc are localized and classified. Each label is propagated along the most significant segments linked to initial vessels. The next labeling phase aims the not processed branches starting from already classified vessels. Only branches and edges at crossings are labeled. Finally, using the current labels set, the uncertain cases are solved.


international symposium on signals, circuits and systems | 2015

A review of several applications of FL in modeling and in 1D/2D signal processing

Vasile Apopei; Silviu-Ioan Bejinariu; Hariton Costin; Doina Jitca; Mihaela Luca; Cristina Diana Nita

The paper is dedicated to the 50 years passed since the theory of fuzzy sets and fuzzy logic was established. This opportunity is used to analyze some research directions in the last decades and to suggest what directions may be fruitful to develop. The paper undertakes the task of reviewing some of our laboratory applications in 1D/2D signal processing. We are referring to the wave propagation fuzzy modeling, the use of fuzzy logic in formant detection and speech synthesis, in Parkinson disease diagnosis using handwriting text analysis and in processing grayscale medical images. Some results not already reported are also shown.


e health and bioengineering conference | 2015

Multimodal biometric authentication based on voice, face and iris

Tudor Barbu; Adrian Ciobanu; Mihaela Luca

A multimodal biometric system is proposed in this paper. Our multimodal biometric authentication solution is based on three identifiers: iris, voice and faces. A mel-cepstral voice recognition is described first. Then, face authentication is approached by using SIFT-based features. Next, LAB-based iris recognition approach is proposed. The biometric fusion is performed at the level of the decision module.


international symposium on signals, circuits and systems | 2017

Video processing for rat behavior analysis

Florin Rotaru; Silviu-Ioan Bejinariu; Mihaela Luca; Ramona Luca; Cristina Diana Nita

A procedure for laboratory rats tracking using image and video processing techniques is proposed. A plastic box split into three chambers by two walls is the analyzed scene. Each experiment starts with a sequence during at least eight minutes with a free rat placed in the middle area with the closed doors to the box marginal locations. The proposed method determines for each sequence frame the location of the rat head. For the second part of the experiment, with open doors, the procedure will be completed later on with the computation of free rat overall motion parameters and identification of specific rat behaviors.

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Anca Ignat

Alexandru Ioan Cuza University

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