Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

Automatic musical instrument recognition for multimedia indexing

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Multimodal automatic user disposition recognition in human-machine interaction

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2013

Segmentation and Recognition of Multi-Food Meal Images for Carbohydrate Counting

In this paper, we propose novel methodologies for the automatic segmentation and recognition of multi-food images. The proposed methods implement the first modules of a carbohydrate counting and insulin advisory system for type 1 diabetic patients. Initially the plate is segmented using pyramidal mean-shift filtering and a region growing algorithm. Then each of the resulted segments is described by both color and texture features and classified by a support vector machine into one of six different major food classes. Finally, a modified version of the Huang and Dom evaluation index was proposed, addressing the particular needs of the food segmentation problem. The experimental results prove the effectiveness of the proposed method achieving a segmentation accuracy of 88.5% and recognition rate equal to 87%

Unsupervised automatic music genre classification

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC

In the first part of this research, three stages were stated for a program to increase the information extracted from ink evidence and maximise its usefulness to the criminal and civil justice system. These stages are (a) develop a standard methodology for analysing ink samples by high-performance thin layer chromatography (HPTLC) in reproducible way, when ink samples are analysed at different time, locations and by different examiners; (b) compare automatically and objectively ink samples; and (c) define and evaluate theoretical framework for the use of ink evidence in forensic context. This report focuses on the second of the three stages. Using the calibration and acquisition process described in the previous report, mathematical algorithms are proposed to automatically and objectively compare ink samples. The performances of these algorithms are systematically studied for various chemical and forensic conditions using standard performance tests commonly used in biometrics studies. The results show that different algorithms are best suited for different tasks. Finally, this report demonstrates how modern analytical and computer technology can be used in the field of ink examination and how tools developed and successfully applied in other fields of forensic science can help maximising its impact within the field of questioned documents.

Common Scientific Lexicon for Automatic Discourse Analysis of Scientific and Technical Texts

The paper reports on preliminary results of an ongoing research aiming at development of an automatic procedure for recognition of discourse-compositional structure of scientific and technical texts, which is required in many NLP applications. The procedure exploits as discourse markers various domain-independent words and expressions that are specific for scientific and technical texts and organize scientific discourse. The paper discusses features of scientific discourse and common scientific lexicon comprising such words and expressions. Methodological issues of development of a computer dictionary for common scientific lexicon are concerned; basic principles of its organization are described as well. Main steps of the discourse-analyzing procedure based on the dictionary and surface syntactical analysis are pointed out.

PHLEBOTOMINE FAUNA (DIPTERA: PSYCHODIDAE) IN AN AREA OF FISHING TOURISM IN CENTRAL-WESTERN BRAZIL

The aim of this study was to identify behavioral aspects of the sandfly fauna of a fishing tourism area in the municipality of Bonito (MS). Monthly captures were undertaken from December 2009 to November 2010, using automatic CDC type light traps, from 18h00 to 06h00, in a forested area, a savannah area, peridomiciles and animal shelters near peridomiciliary areas. Nyssomyia whitmani was the most frequent out of a total of 6,699 specimens collected, belonging to 16 species, followed by Psathyromyia bigeniculata and Lutzomyia longipalpis, found in all the environments investigated, though in their greatest numbers in the animal shelters. Ny. whitmani exhibited its highest frequencies during the dry months, coincident with the fishing season, when the risk of transmission of cutaneous leishmaniasis for tourists and inhabitants increases. Noteworthy was the finding of two species naturally infected by flagellates: Ny. whitmani and Pa. bigeniculata. The local population and visiting tourists should be warned of the threat posed by leishmaniasis and the health authorities alerted to the need for adopting environmental sanitary measures, especially regarding such animal shelters as they seem to provide favorable conditions to the proliferation, maintenance and breeding opportunities of phlebotomines.

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth.

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001.

Multi-scale systems analysis of plant development : beyond cellular signaling and tissue morphodynamics

Les plantes sont essentielles pour les sociétés humaines. Notre alimentation quotidienne, les matériaux de constructions et les sources énergétiques dérivent de la biomasse végétale. En revanche, la compréhension des multiples aspects développementaux des plantes est encore peu exploitée et représente un sujet de recherche majeur pour la science. L'émergence des technologies à haut débit pour le séquençage de génome à grande échelle ou l'imagerie de haute résolution permet à présent de produire des quantités énormes d'information. L'analyse informatique est une façon d'intégrer ces données et de réduire la complexité apparente vers une échelle d'abstraction appropriée, dont la finalité est de fournir des perspectives de recherches ciblées. Ceci représente la raison première de cette thèse. En d'autres termes, nous appliquons des méthodes descriptives et prédictives combinées à des simulations numériques afin d'apporter des solutions originales à des problèmes relatifs à la morphogénèse à l'échelle de la cellule et de l'organe. Nous nous sommes fixés parmi les objectifs principaux de cette thèse d'élucider de quelle manière l'interaction croisée des phytohormones auxine et brassinosteroïdes (BRs) détermine la croissance de la cellule dans la racine du méristème apical d'Arabidopsis thaliana, l'organisme modèle de référence pour les études moléculaires en plantes. Pour reconstruire le réseau de signalement cellulaire, nous avons extrait de la littérature les informations pertinentes concernant les relations entre les protéines impliquées dans la transduction des signaux hormonaux. Le réseau a ensuite été modélisé en utilisant un formalisme logique et qualitatif pour pallier l'absence de données quantitatives. Tout d'abord, Les résultats ont permis de confirmer que l'auxine et les BRs agissent en synergie pour contrôler la croissance de la cellule, puis, d'expliquer des observations phénotypiques paradoxales et au final, de mettre à jour une interaction clef entre deux protéines dans la maintenance du méristème de la racine. Une étude ultérieure chez la plante modèle Brachypodium dystachion (Brachypo- dium) a révélé l'ajustement du réseau d'interaction croisée entre auxine et éthylène par rapport à Arabidopsis. Chez ce dernier, interférer avec la biosynthèse de l'auxine mène à la formation d'une racine courte. Néanmoins, nous avons isolé chez Brachypodium un mutant hypomorphique dans la biosynthèse de l'auxine qui affiche une racine plus longue. Nous avons alors conduit une analyse morphométrique qui a confirmé que des cellules plus anisotropique (plus fines et longues) sont à l'origine de ce phénotype racinaire. Des analyses plus approfondies ont démontré que la différence phénotypique entre Brachypodium et Arabidopsis s'explique par une inversion de la fonction régulatrice dans la relation entre le réseau de signalisation par l'éthylène et la biosynthèse de l'auxine. L'analyse morphométrique utilisée dans l'étude précédente exploite le pipeline de traitement d'image de notre méthode d'histologie quantitative. Pendant la croissance secondaire, la symétrie bilatérale de l'hypocotyle est remplacée par une symétrie radiale et une organisation concentrique des tissus constitutifs. Ces tissus sont initialement composés d'une douzaine de cellules mais peuvent aisément atteindre des dizaines de milliers dans les derniers stades du développement. Cette échelle dépasse largement le seuil d'investigation par les moyens dits 'traditionnels' comme l'imagerie directe de tissus en profondeur. L'étude de ce système pendant cette phase de développement ne peut se faire qu'en réalisant des coupes fines de l'organe, ce qui empêche une compréhension des phénomènes cellulaires dynamiques sous-jacents. Nous y avons remédié en proposant une stratégie originale nommée, histologie quantitative. De fait, nous avons extrait l'information contenue dans des images de très haute résolution de sections transverses d'hypocotyles en utilisant un pipeline d'analyse et de segmentation d'image à grande échelle. Nous l'avons ensuite combiné avec un algorithme de reconnaissance automatique des cellules. Cet outil nous a permis de réaliser une description quantitative de la progression de la croissance secondaire révélant des schémas développementales non-apparents avec une inspection visuelle classique. La formation de pôle de phloèmes en structure répétée et espacée entre eux d'une longueur constante illustre les bénéfices de notre approche. Par ailleurs, l'exploitation approfondie de ces résultats a montré un changement de croissance anisotropique des cellules du cambium et du phloème qui semble en phase avec l'expansion du xylème. Combinant des outils génétiques et de la modélisation biomécanique, nous avons démontré que seule la croissance plus rapide des tissus internes peut produire une réorientation de l'axe de croissance anisotropique des tissus périphériques. Cette prédiction a été confirmée par le calcul du ratio des taux de croissance du xylème et du phloème au cours de développement secondaire ; des ratios élevés sont effectivement observés et concomitant à l'établissement progressif et tangentiel du cambium. Ces résultats suggèrent un mécanisme d'auto-organisation établi par un gradient de division méristématique qui génèrent une distribution de contraintes mécaniques. Ceci réoriente la croissance anisotropique des tissus périphériques pour supporter la croissance secondaire. - Plants are essential for human society, because our daily food, construction materials and sustainable energy are derived from plant biomass. Yet, despite this importance, the multiple developmental aspects of plants are still poorly understood and represent a major challenge for science. With the emergence of high throughput devices for genome sequencing and high-resolution imaging, data has never been so easy to collect, generating huge amounts of information. Computational analysis is one way to integrate those data and to decrease the apparent complexity towards an appropriate scale of abstraction with the aim to eventually provide new answers and direct further research perspectives. This is the motivation behind this thesis work, i.e. the application of descriptive and predictive analytics combined with computational modeling to answer problems that revolve around morphogenesis at the subcellular and organ scale. One of the goals of this thesis is to elucidate how the auxin-brassinosteroid phytohormone interaction determines the cell growth in the root apical meristem of Arabidopsis thaliana (Arabidopsis), the plant model of reference for molecular studies. The pertinent information about signaling protein relationships was obtained through the literature to reconstruct the entire hormonal crosstalk. Due to a lack of quantitative information, we employed a qualitative modeling formalism. This work permitted to confirm the synergistic effect of the hormonal crosstalk on cell elongation, to explain some of our paradoxical mutant phenotypes and to predict a novel interaction between the BREVIS RADIX (BRX) protein and the transcription factor MONOPTEROS (MP),which turned out to be critical for the maintenance of the root meristem. On the same subcellular scale, another study in the monocot model Brachypodium dystachion (Brachypodium) revealed an alternative wiring of auxin-ethylene crosstalk as compared to Arabidopsis. In the latter, increasing interference with auxin biosynthesis results in progressively shorter roots. By contrast, a hypomorphic Brachypodium mutant isolated in this study in an enzyme of the auxin biosynthesis pathway displayed a dramatically longer seminal root. Our morphometric analysis confirmed that more anisotropic cells (thinner and longer) are principally responsible for the mutant root phenotype. Further characterization pointed towards an inverted regulatory logic in the relation between ethylene signaling and auxin biosynthesis in Brachypodium as compared to Arabidopsis, which explains the phenotypic discrepancy. Finally, the morphometric analysis of hypocotyl secondary growth that we applied in this study was performed with the image-processing pipeline of our quantitative histology method. During its secondary growth, the hypocotyl reorganizes its primary bilateral symmetry to a radial symmetry of highly specialized tissues comprising several thousand cells, starting with a few dozens. However, such a scale only permits observations in thin cross-sections, severely hampering a comprehensive analysis of the morphodynamics involved. Our quantitative histology strategy overcomes this limitation. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with an automated cell type recognition algorithm, it allows precise quantitative characterization of vascular development and reveals developmental patterns that were not evident from visual inspection, for example the steady interspace distance of the phloem poles. Further analyses indicated a change in growth anisotropy of cambial and phloem cells, which appeared in phase with the expansion of xylem. Combining genetic tools and computational modeling, we showed that the reorientation of growth anisotropy axis of peripheral tissue layers only occurs when the growth rate of central tissue is higher than the peripheral one. This was confirmed by the calculation of the ratio of the growth rate xylem to phloem throughout secondary growth. High ratios are indeed observed and concomitant with the homogenization of cambium anisotropy. These results suggest a self-organization mechanism, promoted by a gradient of division in the cambium that generates a pattern of mechanical constraints. This, in turn, reorients the growth anisotropy of peripheral tissues to sustain the secondary growth.

Qualified immigrants' success: exploring the motivation to migrate and to integrate

High-quality employees with international experience bring valuable advantages to internationally operating organizations. The growing number and importance of immigrants, and particularly qualified, university-educated immigrants, deserves more attention from international business practitioners and scholars. The market for highly qualified people within MNCs is increasingly becoming international, and ever more of them have migrated to a new country to advance their career. Such employees can be a source of competitive advantage for international firms. We use qualitative research with qualified immigrants (QIs) in France to argue that the success of QIs depends in large part on their motivation to integrate into their host country, which is largely explained by their motivation to migrate. From the qualitative data we derive four different types of qualified migrant, and suggest that the type will determine the success of the immigrant within, and outside, the organization. The relationship between the motivation to migrate and the motivation to integrate is moderated by “met expectations” and “organizational integration policies”, such that the effects of these, in turn, vary with type. Recognition of the types of QI and the moderating factors will be valuable for practitioners, as well as opening up research avenues for scholars.

Reconhecimento de voz através de unidades menores do que a palavra, utilizando Wavelet Packet e SVM, em uma nova estrutura hierárquica de decisão

The automatic speech recognition by machine has been the target of researchers in the past five decades. In this period have been numerous advances, such as in the field of recognition of isolated words (commands), which has very high rates of recognition, currently. However, we are still far from developing a system that could have a performance similar to the human being (automatic continuous speech recognition). One of the great challenges of searches for continuous speech recognition is the large amount of pattern. The modern languages such as English, French, Spanish and Portuguese have approximately 500,000 words or patterns to be identified. The purpose of this study is to use smaller units than the word such as phonemes, syllables and difones units as the basis for the speech recognition, aiming to recognize any words without necessarily using them. The main goal is to reduce the restriction imposed by the excessive amount of patterns. In order to validate this proposal, the system was tested in the isolated word recognition in dependent-case. The phonemes characteristics of the Brazil s Portuguese language were used to developed the hierarchy decision system. These decisions are made through the use of neural networks SVM (Support Vector Machines). The main speech features used were obtained from the Wavelet Packet Transform. The descriptors MFCC (Mel-Frequency Cepstral Coefficient) are also used in this work. It was concluded that the method proposed in this work, showed good results in the steps of recognition of vowels, consonants (syllables) and words when compared with other existing methods in literature

Identificación y reconocimiento de matrículas de automóviles con MATLAB

Este Proyecto Fin de Carrera trata sobre el reconocimiento e identificación de caracteres de matrículas de automóviles. Este tipo de sistemas de reconocimiento también se los conoce mundialmente como sistemas ANPR ("Automatic Number Plate Recognition") o LPR ("License Plate Recognition"). La gran cantidad de vehículos y logística que se mueve cada segundo por todo el planeta, hace necesaria su registro para su tratamiento y control. Por ello, es necesario implementar un sistema que pueda identificar correctamente estos recursos, para su posterior procesado, construyendo así una herramienta útil, ágil y dinámica. El presente trabajo ha sido estructurado en varias partes. La primera de ellas nos muestra los objetivos y las motivaciones que se persiguen con la realización de este proyecto. En la segunda, se abordan y desarrollan todos los diferentes procesos teóricos y técnicos, así como matemáticos, que forman un sistema ANPR común, con el fin de implementar una aplicación práctica que pueda demostrar la utilidad de estos en cualquier situación. En la tercera, se desarrolla esa parte práctica en la que se apoya la base teórica del trabajo. En ésta se describen y desarrollan los diversos algoritmos, creados con el fin de estudiar y comprobar todo lo planteado hasta ahora, así como observar su comportamiento. Se implementan varios procesos característicos del reconocimiento de caracteres y patrones, como la detección de áreas o patrones, rotado y transformación de imágenes, procesos de detección de bordes, segmentación de caracteres y patrones, umbralización y normalización, extracción de características y patrones, redes neuronales, y finalmente el reconocimiento óptico de caracteres o comúnmente conocido como OCR. La última parte refleja los resultados obtenidos a partir del sistema de reconocimiento de caracteres implementado para el trabajo y se exponen las conclusiones extraídas a partir de éste. Finalmente se plantean las líneas futuras de mejora, desarrollo e investigación, para poder realizar un sistema más eficiente y global. This Thesis deals about license plate characters recognition and identification. These kinds of systems are also known worldwide as ANPR systems ("Automatic Number Plate Recognition") or LPR ("License Plate Recognition"). The great number of vehicles and logistics moving every second all over the world, requires a registration for treatment and control. Thereby, it’s therefore necessary to implement a system that can identify correctly these resources, for further processing, thus building a useful, flexible and dynamic tool. This work has been structured into several parts. The first one shows the objectives and motivations attained by the completion of this project. In the second part, it’s developed all the different theoretical and technical processes, forming a common ANPR system in order to implement a practical application that can demonstrate the usefulness of these ones on any situation. In the third, the practical part is developed, which is based on the theoretical work. In this one are described and developed various algorithms, created to study and verify all the questions until now suggested, and complain the behavior of these systems. Several recognition of characters and patterns characteristic processes are implemented, such as areas or patterns detection, image rotation and transformation, edge detection processes, patterns and character segmentation, thresholding and normalization, features and patterns extraction, neural networks, and finally the optical character recognition or commonly known like OCR. The last part shows the results obtained from the character recognition system implemented for this thesis and the outlines conclusions drawn from it. Finally, future lines of improvement, research and development are proposed, in order to make a more efficient and comprehensive system.

Desarrollo de una herramienta para analizar métodos de reconocimiento de emociones

Desde hace más de 20 años, muchos grupos de investigación trabajan en el estudio de técnicas de reconocimiento automático de expresiones faciales. En los últimos años, gracias al avance de las metodologías, ha habido numerosos avances que hacen posible una rápida detección de las caras presentes en una imagen y proporcionan algoritmos de clasificación de expresiones. En este proyecto se realiza un estudio sobre el estado del arte en reconocimiento automático de emociones, para conocer los diversos métodos que existen en el análisis facial y en el reconocimiento de la emoción. Con el fin de poder comparar estos métodos y otros futuros, se implementa una herramienta modular y ampliable y que además integra un método de extracción de características que consiste en la obtención de puntos de interés en la cara y dos métodos para clasificar la expresión, uno mediante comparación de desplazamientos de los puntos faciales, y otro mediante detección de movimientos específicos llamados unidades de acción. Para el entrenamiento del sistema y la posterior evaluación del mismo, se emplean las bases de datos Cohn-Kanade+ y JAFFE, de libre acceso a la comunidad científica. Después, una evaluación de estos métodos es llevada a cabo usando diferentes parámetros, bases de datos y variando el número de emociones. Finalmente, se extraen conclusiones del trabajo y su evaluación, proponiendo las mejoras necesarias e investigación futura. ABSTRACT. Currently, many research teams focus on the study of techniques for automatic facial expression recognition. Due to the appearance of digital image processing, in recent years there have been many advances in the field of face detection, feature extraction and expression classification. In this project, a study of the state of the art on automatic emotion recognition is performed to know the different methods existing in facial feature extraction and emotion recognition. To compare these methods, a user friendly tool is implemented. Besides, a feature extraction method is developed which consists in obtaining 19 facial feature points. Those are passed to two expression classifier methods, one based on point displacements, and one based on the recognition of facial Action Units. Cohn-Kanade+ and JAFFE databases, both freely available to the scientific community, are used for system training and evaluation. Then, an evaluation of the methods is performed with different parameters, databases and varying the number of emotions. Finally, conclusions of the work and its evaluation are extracted, proposing some necessary improvements and future research.