Graled (Grapevine leaf digitalization) Software for the Detection and Graphic Reconstruction of Ampelometric Differences Between Vitis Leaves

Raster graphic ampelometric software was not exclusively developed for the estimation of leaf area, but also for the characterization of grapevine (Viti vinifera L.) leaves. The software was written in C-Hprogramming language, using the C-1-1- Builder 2007 for Windows 95-XP and Linux operation systems. It handles desktop-scanned images. On the image analysed with the GRA.LE.D., the user has to determine 11 points. These points are then connected and the distances between them calculated. The GRA.LE.D. software supports standard ampelometric measurements such as leaf area, angles between the veins and lengths of the veins. These measurements are recorded by the software and exported into plain ASCII text files for single or multiple samples. Twenty-two biometric data points of each leaf are identified by the GRA.LE.D. It presents the opportunity to statistically analyse experimental data, allows comparison of cultivars and enables graphic reconstruction of leaves using the Microsoft Excel Chart Wizard. The GRA. LE.D. was thoroughly calibrated and compared to other widely used instruments and methods such as photo-gravimetry, LiCor L0100, WinDIAS2.0 and ImageTool. By comparison, the GRA.LE.D. presented the most accurate measurements of leaf area, but the LiCor L0100 and the WinDIAS2.0 were faster, while the photo-gravimetric method proved to be the most time-consuming. The WinDIAS2.0 instrument was the least reliable. The GRA.LE.D. is uncomplicated, user-friendly, accurate, consistent, reliable and has wide practical application.

Thermal imaging as a biometrics approach to facial signature authentication

This dissertation develops an image processing framework with unique feature extraction and similarity measurements for human face recognition in the thermal mid-wave infrared portion of the electromagnetic spectrum. The goals of this research is to design specialized algorithms that would extract facial vasculature information, create a thermal facial signature and identify the individual. The objective is to use such findings in support of a biometrics system for human identification with a high degree of accuracy and a high degree of reliability. This last assertion is due to the minimal to no risk for potential alteration of the intrinsic physiological characteristics seen through thermal infrared imaging. The proposed thermal facial signature recognition is fully integrated and consolidates the main and critical steps of feature extraction, registration, matching through similarity measures, and validation through testing our algorithm on a database, referred to as C-X1, provided by the Computer Vision Research Laboratory at the University of Notre Dame. Feature extraction was accomplished by first registering the infrared images to a reference image using the functional MRI of the Brain’s (FMRIB’s) Linear Image Registration Tool (FLIRT) modified to suit thermal infrared images. This was followed by segmentation of the facial region using an advanced localized contouring algorithm applied on anisotropically diffused thermal images. Thermal feature extraction from facial images was attained by performing morphological operations such as opening and top-hat segmentation to yield thermal signatures for each subject. Four thermal images taken over a period of six months were used to generate thermal signatures and a thermal template for each subject, the thermal template contains only the most prevalent and consistent features. Finally a similarity measure technique was used to match signatures to templates and the Principal Component Analysis (PCA) was used to validate the results of the matching process. Thirteen subjects were used for testing the developed technique on an in-house thermal imaging system. The matching using an Euclidean-based similarity measure showed 88% accuracy in the case of skeletonized signatures and templates, we obtained 90% accuracy for anisotropically diffused signatures and templates. We also employed the Manhattan-based similarity measure and obtained an accuracy of 90.39% for skeletonized and diffused templates and signatures. It was found that an average 18.9% improvement in the similarity measure was obtained when using diffused templates. The Euclidean- and Manhattan-based similarity measure was also applied to skeletonized signatures and templates of 25 subjects in the C-X1 database. The highly accurate results obtained in the matching process along with the generalized design process clearly demonstrate the ability of the thermal infrared system to be used on other thermal imaging based systems and related databases. A novel user-initialization registration of thermal facial images has been successfully implemented. Furthermore, the novel approach at developing a thermal signature template using four images taken at various times ensured that unforeseen changes in the vasculature did not affect the biometric matching process as it relied on consistent thermal features.

Determination of signature volatile odor chemicals emanating from novel biological specimens by non-invasive analytical techniques for the potential use in forensic identifications

Human scent, or the volatile organic compounds (VOCs) produced by an individual, has been recognized as a biometric measurement because of the distinct variations in both the presence and abundance of these VOCs between individuals. In forensic science, human scent has been used as a form of associative evidence by linking a suspect to a scene/object through the use of human scent discriminating canines. The scent most often collected and used with these specially trained canines is from the hands because a majority of the evidence collected is likely to have been handled by the suspect. However, the scents from other biological specimens, especially those that are likely to be present at scenes of violent crimes, have yet to be explored. Hair, fingernails and saliva are examples of these types of specimens. ^ In this work, a headspace solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) technique was used for the identification of VOCs from hand odor, hair, fingernails and saliva. Sixty individuals were sampled and the profiles of the extracted VOCs were evaluated to assess whether they could be used for distinguishing individuals. Preliminary analysis of the biological specimens collected from an individual (intra-subject) showed that, though these materials have some VOCs in common, their overall chemical profile is different for each specimen type. Pair-wise comparisons, using Spearman Rank correlations, were made between the chemical profiles obtained from each subject, per a specimen type. Greater than 98.8% of the collected samples were distinguished from the subjects for all of the specimen types, demonstrating that these specimens can be used for distinguishing individuals. ^ Additionally, field trials were performed to determine the utility of these specimens as scent sources for human scent discriminating canines. Three trials were conducted to evaluate hair, fingernails and saliva in comparison to hand odor, which was considered the standard source of human odor. It was revealed that canines perform similarly to these alternative human scent sources as they do to hand odor implying that, though there are differences in the chemical profiles released by these specimens, they can still be used for the discrimination of individuals by trained canines.^

Algoritmo papílio como método de proteção de templates para aumentar a segurança em sistemas de identificação biométricos

There are authentication models which use passwords, keys, personal identifiers (cards, tags etc) to authenticate a particular user in the authentication/identification process. However, there are other systems that can use biometric data, such as signature, fingerprint, voice, etc., to authenticate an individual in a system. In another hand, the storage of biometric can bring some risks such as consistency and protection problems for these data. According to this problem, it is necessary to protect these biometric databases to ensure the integrity and reliability of the system. In this case, there are models for security/authentication biometric identification, for example, models and Fuzzy Vault and Fuzzy Commitment systems. Currently, these models are mostly used in the cases for protection of biometric data, but they have fragile elements in the protection process. Therefore, increasing the level of security of these methods through changes in the structure, or even by inserting new layers of protection is one of the goals of this thesis. In other words, this work proposes the simultaneous use of encryption (Encryption Algorithm Papilio) with protection models templates (Fuzzy Vault and Fuzzy Commitment) in identification systems based on biometric. The objective of this work is to improve two aspects in Biometric systems: safety and accuracy. Furthermore, it is necessary to maintain a reasonable level of efficiency of this data through the use of more elaborate classification structures, known as committees. Therefore, we intend to propose a model of a safer biometric identification systems for identification.

A probabilistic analysis of the biometrics menagerie existence: case study in fingerprint data

Until recently the use of biometrics was restricted to high-security environments and criminal identification applications, for economic and technological reasons. However, in recent years, biometric authentication has become part of daily lives of people. The large scale use of biometrics has shown that users within the system may have different degrees of accuracy. Some people may have trouble authenticating, while others may be particularly vulnerable to imitation. Recent studies have investigated and identified these types of users, giving them the names of animals: Sheep, Goats, Lambs, Wolves, Doves, Chameleons, Worms and Phantoms. The aim of this study is to evaluate the existence of these users types in a database of fingerprints and propose a new way of investigating them, based on the performance of verification between subjects samples. Once introduced some basic concepts in biometrics and fingerprint, we present the biometric menagerie and how to evaluate them.

A probabilistic analysis of the biometrics menagerie existence: case study in fingerprint data

Until recently the use of biometrics was restricted to high-security environments and criminal identification applications, for economic and technological reasons. However, in recent years, biometric authentication has become part of daily lives of people. The large scale use of biometrics has shown that users within the system may have different degrees of accuracy. Some people may have trouble authenticating, while others may be particularly vulnerable to imitation. Recent studies have investigated and identified these types of users, giving them the names of animals: Sheep, Goats, Lambs, Wolves, Doves, Chameleons, Worms and Phantoms. The aim of this study is to evaluate the existence of these users types in a database of fingerprints and propose a new way of investigating them, based on the performance of verification between subjects samples. Once introduced some basic concepts in biometrics and fingerprint, we present the biometric menagerie and how to evaluate them.

Biometria de frutos e sementes, crescimento e produção de mudas de Campomanesia adamantium Blume e Campomanesia pubescens O. Berg

Campomanesia adamantium and Campomanesia pubescens are morphologically similar, occur in the same regions of the Cerrado, are difficult to differentiate and exhibit naturally slow growth and development. The objectives of this study were to analyze fruit and seed biometric data, emergence capacity and seedling growth characteristics. Fruit from both species was collected and used to measure biometric data of the fruit and seeds and to set up two emergence and two seedling growth experiments. C. adamantium fruit is round and has wider, pale yellow seeds while C. pubescens fruit is ellipsoidal to pyriform with yellow gold seeds. C. adamantium’s greater fresh fruit mass and biometric variability favors selection of promising material for commercialization. Seed drying reduced the speed and rate of seedling emergence of C. adamantium, but had no effect on C. pubescens. Leaf number, height, shoot dry weight and the ratio of shoot dry weight to root dry weight were greater in C. adamantium than in the slower growing C. pubescens. Increases in substrate volume favor seedling development. Slow-release fertilizer application at 1g per 115 cm3 substrate increased leaf formation, plant height and shoot dry weight of seedlings of both species and lateral budding in C. adamantium. Until 120 days after transplant, lateral budding was not observed in C. pubescens seedlings. For all traits evaluated in this experiment, C. adamantium seedling growth was greater than that of C. pubescens.

Influência das alturas iniciais de pasto diferido na recria de cordeiros sobre o desempenho na terminação em confinamento

The objective of this study was to evaluate the productive performance, metabolic and feeding behavior of sheep after ninety days deferred pasture at different heights. The experiment was conducted at Capim Branco experimental farm of the Universidade Federal de Uberlândia. During the period of 90 days, from June to September 2013, forty-eight crossbred lambs Santa Inês x Dorper, divided into groups of four animals, occupied twelve pickets deferred pasture with four initial heights (15 cm, 25 cm, 35 cm and 45 cm). During this period we evaluated the structural characteristics of pasture. For confinement, from September to December 2013, 32 of these animals were used (16 males and 16 females), divided into four bays, separated as pasture were using. The consumption was assessed daily, while biometric measurements were made every 21 days. In relation to gender, there were differences in average daily gain weight. Reviews of feeding behavior occurred at the beginning, middle and end of the experiment for 24 hours. The rumination and leisure activities do not present statistical differences, both initial height of pasture and by period. The time spent on intake was higher during the daytime both treatments starting height as the experimental periods, however, rumination activity was more intense at night. Blood glucose was achieved in five periods of the day, while other metabolites have been obtained with a collection made fortnightly. The different initial heights not promoted effects on blood glucose. The harvesting times were not affected. However, there was a reduction of basal blood glucose of animals throughout the experimental period. There was a significant interaction between the initial pasture heights and periods of evaluation of basal glucose. Cholesterol and triglyceride levels were below recommended levels, however the final phase of confinement cholesterol level increased significantly. The values of VLDL and GGT were above the reference range. FA and AST showed average values within the recommended values. Total protein was influenced by different initial heights of pasture. The creatinine and albumin had values below the recommended range. Moreover, the albumin decreased during the confinement time. Uric acid showed close to the recommended maximum. There was stabilization of compensatory growth, with modification of consumption and weight gain at 45 days of experiment.

Detection of frontal faces in video streams

[EN]This paper describes an approach for detection of frontal faces in real time (20-35Hz) for further processing. This approach makes use of a combination of previous detection tracking and color for selecting interest areas. On those areas, later facial features such as eyes, nose and mouth are searched based on geometric tests, appearance veri cation, temporal and spatial coherence. The system makes use of very simple techniques applied in a cascade approach, combined and coordinated with temporal information for improving performance. This module is a component of a complete system designed for detection, tracking and identi cation of individuals [1].

An incremental learning algorithm for face recognition

[EN]In face recognition, where high-dimensional representation spaces are generally used, it is very important to take advantage of all the available information. In particular, many labelled facial images will be accumulated while the recognition system is functioning, and due to practical reasons some of them are often discarded. In this paper, we propose an algorithm for using this information. The algorithm has the fundamental characteristic of being incremental. On the other hand, the algorithm makes use of a combination of classification results for the images in the input sequence. Experiments with sequences obtained with a real person detection and tracking system allow us to analyze the performance of the algorithm, as well as its potential improvements.

Construcción de índices de biomasa para los recursos anchoveta (Engraulis ringens) y jurel (Trachurus murphyi) del Ecosistema de afloramiento peruano usando modelos empíricos basados en información acústica

Los principales recursos pesqueros pelágicos de interés económico en el Perú son anchoveta (Engraulis ringens), jurel (Trachurus murphyi) y caballa (Scomber japonicus) [3]. Para su evaluación, se lleva a cabo cruceros de evaluación acústica en los que se integra información de ecoabundancia y proporción de tallas por especie para obtener valores de biomasa y abundancia. Sin embargo, para especies no objetivo (como jurel), dichos valores resultan poco confiables por la lejanía entre los puntos de muestreo biométrico y acústico. Para resolver este inconveniente, el presente trabajo propuso utilizar modelos empíricos (de tipo GAM y GLM) integrando variables ambientales y de seguimiento de desembarques con la finalidad de generar índices relativos y absolutos para anchoveta y jurel en el período de 1996-2013 dentro del área de las 200 mn frente a la costa peruana. Los resultados obtenidos realzaron la importancia de los lances de comprobación para la obtención de estimaciones robustas de biomasa. Así mismo, se observó que, para anchoveta, los modelos empíricos sí produjeron un buen índice relativo y absoluto, mejorando la utilización de la ecoabundancia por sí sola. Para jurel, sin embargo, el modelo final calibrado resultó en la obtención de un mejor índice relativo. Se recomienda además, la obtención de información de tallas y pesos medios de desembarques para jurel con la finalidad de mejorar las estimaciones de biomasa y abundancia.

Entropy feature extraction of EEG signals for automatic person identification

The use of human brain electroencephalography (EEG) signals for automatic person identi cation has been investigated for a decade. It has been found that the performance of an EEG-based person identication system highly depends on what feature to be extracted from multi-channel EEG signals. Linear methods such as Power Spectral Density and Autoregressive Model have been used to extract EEG features. However these methods assumed that EEG signals are stationary. In fact, EEG signals are complex, non-linear, non-stationary, and random in nature. In addition, other factors such as brain condition or human characteristics may have impacts on the performance, however these factors have not been investigated and evaluated in previous studies. It has been found in the literature that entropy is used to measure the randomness of non-linear time series data. Entropy is also used to measure the level of chaos of braincomputer interface systems. Therefore, this thesis proposes to study the role of entropy in non-linear analysis of EEG signals to discover new features for EEG-based person identi- cation. Five dierent entropy methods including Shannon Entropy, Approximate Entropy, Sample Entropy, Spectral Entropy, and Conditional Entropy have been proposed to extract entropy features that are used to evaluate the performance of EEG-based person identication systems and the impacts of epilepsy, alcohol, age and gender characteristics on these systems. Experiments were performed on the Australian EEG and Alcoholism datasets. Experimental results have shown that, in most cases, the proposed entropy features yield very fast person identication, yet with compatible accuracy because the feature dimension is low. In real life security operation, timely response is critical. The experimental results have also shown that epilepsy, alcohol, age and gender characteristics have impacts on the EEG-based person identication systems.

Características tecnológicas de espécies de pescado com potencial de criação na região sudoeste do Paraná

The fish meat has a particular chemical composition which gives its high nutritional value. However, this food is identified for being highly perishable and this aspect is often named as a barrier to fish consumption. The southwestern Paraná region, parallel to the country's reality, it is characterized by low fish consumption; and one of the strategies aimed at increasing the consumption of this important protein source is encouraging the production of other species besides tilapia. Within this context, it is necessary to know about the meat characteristics. In this sense, the objective of this study was to evaluate the technological potential of pacu, grass carp and catfish species. To do so, at first, it was discussed the chemical and biometric assessment under two distinct descriptive statistical methods, of the three species; and it was also evaluated the discriminating capacity of the study. In a second moment, an evaluation of effects done by two different processes of washing (acid and alkaline) regarding the removal of nitrogen compounds, pigments and the emulsifying ability of the proteins contained in the protein base obtained. Finally, in the third phase, it was aimed to realize the methodology optimization in GC-MS for the analysis geosmin and MIB (2-metilisoborneol) compounds that are responsible for taste/smell of soil and mold in freshwater fish. The results showed a high protein and low lipid content for the three species. The comparison between means and medians revealed symmetry only for protein values and biometric measurements. Lipids, when evaluated only by the means, overestimate the levels for all species. Correlations between body measurements and fillet yield had low correlation, regardless of the species analyzed, and the best prediction equation relates the total weight and fillet weight. The biometric variables were the best discriminating among the species. The evaluation of the washings, it was found that the acidic and basic processes were equally (p ≥ 0.05) efficient (p ≤ 0.05) for the removal of nitrogen compounds on the fish pulps. Regarding the extraction of pigments, a removal efficiency was recorded only for the pacu species, the data were assessed by the parameters L *, a *, b *. When evaluated by the total color difference (ΔE) before and after washing for both processes (acid/alkaline) the ΔE proved feasible perceived by naked eye for all species. The catfish was characterized as the fish that presents the clearest meat with the basic washing considered the most effective in removing pigments for this species. Protein bases obtained by alkaline washes have higher emulsifying capacity (p ≤ 0.05) when compared to unwashed and washed in acid process pulps. The methodology applied for the quantification of MIB and geosmin, allowed to establish that the method of extraction and purification of analytes had low recovery and future studies should be developed for identification and quantification of MIB and geosmin on fish samples.