Hough Transform Approach to Identification of Flare Stars in Multi-exposure Plate Images

ACM Computing Classification System (1998): I.2.8 , I.2.10, I.5.1, J.2.

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%

Automatic Orientation of Multi-Scale Terrestrial Images for 3D Reconstruction

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Quantitative analysis of multi-spectral fundus images

We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised by the concentrations of the five main absorbers found in the fundus: retinal haemoglobins, choroidal haemoglobins, choroidal melanin, RPE melanin and macular pigment. These parameters are shown to give rise to distinct variations in the tissue colouration. We use the results of the Monte Carlo simulations to construct an inverse model which maps tissue colouration onto the model parameters. This allows the concentration and distribution of the five main absorbers to be determined from suitable multi-spectral images. We propose the use of "image quotients" to allow this information to be extracted from uncalibrated image data. The filters used to acquire the images are selected to ensure a one-to-one mapping between model parameters and image quotients. To recover five model parameters uniquely, images must be acquired in six distinct spectral bands. Theoretical investigations suggest that retinal haemoglobins and macular pigment can be recovered with RMS errors of less than 10%. We present parametric maps showing the variation of these parameters across the posterior pole of the fundus. The results are in agreement with known tissue histology for normal healthy subjects. We also present an early result which suggests that, with further development, the technique could be used to successfully detect retinal haemorrhages.

Minimum Mean Square Error Approach in Images Processing for Full-field Displacements and Deformation Measurements

A vision system is applied to full-field displacements and deformation measurements in solid mechanics. A speckle like pattern is preliminary formed on the surface under investigation. To determine displacements field of one speckle image with respect to a reference speckle image, sub-images, referred to Zones Of Interest (ZOI) are considered. The field is obtained by matching a ZOI in the reference image with the respective ZOI in the moved image. Two image processing techniques are used for implementing the matching procedure: – cross correlation function and minimum mean square error (MMSE) of the ZOI intensity distribution. The two algorithms are compared and the influence of the ZOI size on the accuracy of measurements is studied.

Classification multi-échelle d'images à très haute résolution spatiale basée sur une nouvelle approche texturale

Résumé : Face à l’accroissement de la résolution spatiale des capteurs optiques satellitaires, de nouvelles stratégies doivent être développées pour classifier les images de télédétection. En effet, l’abondance de détails dans ces images diminue fortement l’efficacité des classifications spectrales; de nombreuses méthodes de classification texturale, notamment les approches statistiques, ne sont plus adaptées. À l’inverse, les approches structurelles offrent une ouverture intéressante : ces approches orientées objet consistent à étudier la structure de l’image pour en interpréter le sens. Un algorithme de ce type est proposé dans la première partie de cette thèse. Reposant sur la détection et l’analyse de points-clés (KPC : KeyPoint-based Classification), il offre une solution efficace au problème de la classification d’images à très haute résolution spatiale. Les classifications effectuées sur les données montrent en particulier sa capacité à différencier des textures visuellement similaires. Par ailleurs, il a été montré dans la littérature que la fusion évidentielle, reposant sur la théorie de Dempster-Shafer, est tout à fait adaptée aux images de télédétection en raison de son aptitude à intégrer des concepts tels que l’ambiguïté et l’incertitude. Peu d’études ont en revanche été menées sur l’application de cette théorie à des données texturales complexes telles que celles issues de classifications structurelles. La seconde partie de cette thèse vise à combler ce manque, en s’intéressant à la fusion de classifications KPC multi-échelle par la théorie de Dempster-Shafer. Les tests menés montrent que cette approche multi-échelle permet d’améliorer la classification finale dans le cas où l’image initiale est de faible qualité. De plus, l’étude effectuée met en évidence le potentiel d’amélioration apporté par l’estimation de la fiabilité des classifications intermédiaires, et fournit des pistes pour mener ces estimations.

Distributed processing of large remote sensing images using MapReduce - A case of Edge Detection

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Influence of magnetic field strength and image registration strategy on voxel-based morphometry in a study of Alzheimer's disease.

Multi-centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non-quantitative character of the widely used structural T1-weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi-site MR images, there are only sparse empirically-based recommendations for processing and analysis of pooled multi-centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel-based morphometry in AD. We perform a whole-brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi-centre VBM studies irrespective of disease status or MFS.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Wood Volume Measurement Using Color Images

Tämä työ käsittelee puutukkien tilavuuden mittaamista värikonenäön avulla. Värikuvat on saatu Simpeleellä olevan metsäteollisuusyrityksen hiomosta. Työssä esitetään perusteellisesti matemaattinen teoria, joka liittyy käytettyihin kuvankäsittelymenetelmiin, kuten luokitteluun, kohinan poistoon ja tukkien segmentointiin. Esitetyt menetelmät implementointiin käytännössä ja eri menetelmillä saatuja tuloksia vertailtiin keskenään. Kuvankäsittelyalgoritmit on implementoitu Matlab 6.0:n avulla. Pääasiassa käytettiin uusinta Image Processing Toolboxia, joka on versio 3.0. Tämä työn näkökulma on pääasiassa käytäntöön soveltava, koska metsäteollsuus on korkealla tasolla Suomessa ja siellä on paljon alan yrityksiä, joissa tässä työssä kehitettyä menetelmää voidaan hyödyntää.

Deep radio images of the HEGRA and Whipple TeV sources in the Cygnus OB2 region.

The modern generation of Cherenkov telescopes has revealed a new population of gamma-ray sources in the Galaxy. Some of them have been identified with previously known X-ray binary systems while other remain without clear counterparts a lower energies. Our initial goal here was reporting on extensive radio observations of the first extended and yet unidentified source, namely TeV J2032+4130. This object was originally detected by the HEGRA telescope in the direction of the Cygnus OB2 region and its nature has been a matter of debate during the latest years. The situation has become more complex with the Whipple and MILAGRO telescopes new TeV detections in the same field which could be consistent with the historic HEGRA source, although a different origin cannot be ruled out. Aims.We aim to pursue our radio exploration of the TeV J2032+4130 position that we initiated in a previous paper but taking now into account the latest results from new Whipple and MILAGRO TeV telescopes. The data presented here are an extended follow up of our previous work. Methods.Our investigation is mostly based on interferometric radio observations with the Giant Metre Wave Radio Telescope (GMRT) close to Pune (India) and the Very Large Array (VLA) in New Mexico (USA). We also conducted near infrared observations with the 3.5 m telescope and the OMEGA2000 camera at the Centro Astronómico Hispano Alemán (CAHA) in Almería (Spain). Results.We present deep radio maps centered on the TeV J2032+4130 position at different wavelengths. In particular, our 49 and 20 cm maps cover a field of view larger than half a degree that fully includes the Whipple position and the peak of MILAGRO emission. Our most important result here is a catalogue of 153 radio sources detected at 49 cm within the GMRT antennae primary beam with a full width half maximum (FWHM) of 43 arc-minute. Among them, peculiar sources inside the Whipple error ellipse are discussed in detail, including a likely double-double radio galaxy and a one-sided jet source of possible blazar nature. This last object adds another alternative counterpart possibility to be considered for both the HEGRA, Whipple and MILAGRO emission. Moreover, our multi-configuration VLA images reveal the non-thermal extended emission previously reported by us with improved angular resolution. Its non-thermal spectral index is also confirmed thanks to matching beam observations at the 20 and 6 cm wavelengths.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

An automatic correction method for the heel effect in digitized mammography images

The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode-cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode-anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode-cathode axis and 2.02 mm parallel to the anode-cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.

Estoque de biomassa e carbono florestal em unidades de paisagem na Amazônia: uma análise a partir da abordagem metodológica ecologia da paisagem

O presente trabalho tem por objetivo central demonstrar a variabilidade existente na floresta no que tange aos estoques de biomassa e carbono florestal acima do solo, a partir da identificação e caracterização, com base em técnicas de sensoriamento remoto, de unidades de paisagem em uma área situada no município de Belterra, região oeste do Estado do Pará, a partir da matriz teórico-conceitual da abordagem Ecologia da Paisagem. Para o alcance de tal proposição, a metodologia empregada partiu da revisão da literatura sobre o tema, aquisição de dados cartográficos e orbitais, uso de técnicas de sensoriamento remoto, coleta de dados em campo, tratamento e análise estatística. O trabalho está dividido em quatro capítulos, seguidos pelas considerações gerais da obra. Partindo da matriz teórico-metodológica da Ecologia da Paisagem, analisa-se a dinâmica socioambiental do município de Belterra, que atualmente experimenta a expansão das atividades agrícolas, com destaque para a agricultura mecanizada da soja. A partir da análise multitemporal de imagens Landsat do município pôde-se avaliar a distribuição da cobertura florestal existente no mesmo, bem como o padrão espacial de distribuição das principais unidades de paisagem identificadas. Considerando esse recorte, realizou-se a coleta de dados em campo via inventário florestal em quatro tipologias florestais (floresta de alto platô, floresta de baixo platô, vegetação secundária e tensão ecológica) para obtenção de parâmetros morfométricos da vegetação e posterior quantificação dos estoques de biomassa e carbono contidos em cada unidade, bem como observar o comportamento estrutural da floresta nas mesmas. A adoção da paisagem como escala espacial de análise mostrou-se bastante satisfatória na quantificação dos estoques de biomassa e carbono florestal ao permitir considerar a influência da dinâmica socioeconômica na redução desses estoques. Além disso, possibilitou constatar que o reconhecimento da heterogeneidade da cobertura florestal é um elemento fundamental para a obtenção de estimativas de carbono de acordo com as características estruturais da vegetação, que varia de acordo com a topografia do terreno, com as espécies existentes e com as características geográficas, o que envolve a tipologia climática, as características geomorfológicas, pedológicas e geológicas da área.

Charakteristika und zeitliche Merkmale des Blickrichtungsnacheffekts

In der vorliegenden Arbeit werden verschiedene, insbesondere zeitliche Aspekte des Blickrichtungsnacheffekts (gaze aftereffect) untersucht. Dieser Effekt besagt, dass nach längerer Betrachtung von Bildern, die Personen mit abgewandtem Blick zeigen, die Wahrnehmung von Blickrichtungen in Richtung des adaptierten Blickes verschoben ist. Betrachter halten dann zugewandte Blicke fälschlicherweise für in die Gegenrichtung verschoben, und Blicke in die Adaptationsblickrichtung fälschlicherweise für geradeaus, d.h. sie fühlen sich angeschaut, obwohl sie es nicht werden. In dieser Dissertation wird der Blickrichtungsnacheffekt mit vier psychophysischen Experimenten untersucht, in denen die Probanden einfache kategoriale Urteile über die Blickrichtung der Testbilder abzugeben hatten.rnrnDas erste Experiment untersucht die Induktion des Blickrichtungsnacheffekts. Es wird gezeigt, dass keine separate Adaptationsphase für die Induktion des Nacheffekts notwendig ist. Auch die alleinige, relativ kurze Darbietung des zur Adaptation verwendeten Reizes (TopUp-Display) vor der Präsentation eines Testbildes führt im Laufe wiederholter experimenteller Darbietungen zu einer Verschiebung der allgemeinen Blickrichtungs-Tuningkurve, sowie zu ihrer Verbreiterung. In einem zweiten Experiment wird nachgewiesen, dass die Ausprägung des Blickrichtungsnacheffekts von der jeweiligen Darbietungszeit des Adaptationsreizes abhängt. Zwar ist der Nacheffekt umso stärker, je länger das TopUp-Display gezeigt wird. Aber auch bei sehr kurzen Darbietungszeiten von einer Sekunde kommt der Effekt bereits zustande, hier zeigt sich eine lokal begrenztere Wirkung. Die Auswertung des zeitlichen Verlaufs ergibt, dass sich der Effekt rasch vollständig aufbaut und bereits innerhalb der ersten Darbietungen entsteht. Das dritte Experiment zeigt, dass dem Nacheffekt sowohl kurzfristige Einwirkungen der direkt vor dem Testbild erfolgten Reizung zugrunde liegen, als auch langfristige Memory-Effekte, die über die im Laufe des Experiments gegebenen Wiederholungen akkumuliert werden. Bei Blickwinkeln von 5° halten sich kurzfristige und langfristige Einwirkungen in etwa die Waage. Bei Blickwinkeln von 10° aber sind nur knapp 20% kurzfristig, und etwa 80% langfristige Einwirkungen für den Effekt verantwortlich. In einem vierten Experiment wird die zeitliche Rückbildung des Effekts untersucht und gezeigt, dass sich der Blickrichtungsnacheffekt im Kontrast zu seiner schnellen Entstehung langsam, nämlich innerhalb mehrerer Minuten zurückbildet.rnrnDie Diskussion der Ergebnisse kommt zu dem Schluss, dass die hier gefundene zeitliche Dynamik des Blickrichtungsnacheffekts Adaptationsprozesse auf höheren Schichten der visuellen Informationsverarbeitung als die zugrunde liegenden Mechanismen nahe legt.