Plane detection from monocular image sequences

AIRES, Kelson R. T. ; ARAÚJO, Hélder J. ; MEDEIROS, Adelardo A. D. . Plane Detection from Monocular Image Sequences. In: VISUALIZATION, IMAGING AND IMAGE PROCESSING, 2008, Palma de Mallorca, Spain. Proceedings..., Palma de Mallorca: VIIP, 2008

A User Interaction Bug Analyzer Based on Image

Context: Mobile applications support a set of user-interaction features that are independent of the application logic. Rotating the device, scrolling, or zooming are examples of such features. Some bugs in mobile applications can be attributed to user-interaction features. Objective: This paper proposes and evaluates a bug analyzer based on user-interaction features that uses digital image processing to find bugs. Method: Our bug analyzer detects bugs by comparing the similarity between images taken before and after a user-interaction. SURF, an interest point detector and descriptor, is used to compare the images. To evaluate the bug analyzer, we conducted a case study with 15 randomly selected mobile applications. First, we identified user-interaction bugs by manually testing the applications. Images were captured before and after applying each user-interaction feature. Then, image pairs were processed with SURF to obtain interest points, from which a similarity percentage was computed, to finally decide whether there was a bug. Results: We performed a total of 49 user-interaction feature tests. When manually testing the applications, 17 bugs were found, whereas when using image processing, 15 bugs were detected. Conclusions: 8 out of 15 mobile applications tested had bugs associated to user-interaction features. Our bug analyzer based on image processing was able to detect 88% (15 out of 17) of the user-interaction bugs found with manual testing.

Wind turbine rotor blade monitoring using digital image correlation: a comparison to aeroelastic simulations of a multi-megawatt wind turbine

Optical full-field measurement methods such as Digital Image Correlation (DIC) provide a new opportunity for measuring deformations and vibrations with high spatial and temporal resolution. However, application to full-scale wind turbines is not trivial. Elaborate preparation of the experiment is vital and sophisticated post processing of the DIC results essential. In the present study, a rotor blade of a 3.2 MW wind turbine is equipped with a random black-and-white dot pattern at four different radial positions. Two cameras are located in front of the wind turbine and the response of the rotor blade is monitored using DIC for different turbine operations. In addition, a Light Detection and Ranging (LiDAR) system is used in order to measure the wind conditions. Wind fields are created based on the LiDAR measurements and used to perform aeroelastic simulations of the wind turbine by means of advanced multibody codes. The results from the optical DIC system appear plausible when checked against common and expected results. In addition, the comparison of relative out-of-plane blade deflections shows good agreement between DIC results and aeroelastic simulations.

Effect of grape seed extract on oxidative, color and sensory stability of pre-cooked, frozen, re-heated beef sausage model system

The processing of meats at the factory level can trigger the onset of lipid oxidation, which can lead to meat quality deterioration. Warmed over flavor is an off-flavor, which is associated with oxidative deterioration in meat. To avoid or delay the auto-oxidation process in meat products, synthetic and natural antioxidants have been successfully used. Grape (Vitis Vinifera) is of special interest due to its high content of phenolic compounds. Grape seed extract sold commercially as a dietary supplement, has the potential to reduce lipid oxidation and WOF in cooked ground beef when added at 1%. The objective of study 1 was to compare the antioxidant activity of natural antioxidants including grape seed extract and some herbs belonging to the Lamiaciae family: rosemary (Rosmarinus Officinalis), sage (Salvia Officinalis) and oregano (Origanum Vulgare) with commercial synthetic antioxidants like BHT, BHA, propyl gallate and ascorbic acid using the ORAC assay. All sample solutions were prepared to contain 1.8 gm sample/10 ml solvent. The highest antioxidant activity was observed for the grape seed extract sample (359.75 µM TE), while the lowest was observed for BHA, propyl gallate and rosemary also showed higher antioxidant potential with ORAC values above 300 μmol TE/g. ORAC values obtained for ascorbic acid and Sage were between 250-300μ mol TE/g while lowest values were obtained for Butylated Hydroxytoluene (28.50 µM TE). Based on the high ORAC values obtained for grape seed extract, we can conclude that byproducts of the wine/grape industry have antioxidant potential comparable to or better than those present in synthetic counterparts. The objective of study 2 was to compare three levels of grape seed extract (GSE) to commonly used antioxidants in a pre-cooked, frozen, stored beef and pork sausage model system. Antioxidants added for comparison with control included grape seed extract (100, 300, 500 ppm), ascorbic acid (AA, 100 ppm of fat) and propyl gallate (PG, 100 ppm of fat). Product was formed into rolls, frozen, sliced into patties, cooked on a flat griddle to 70C, overwrapped in PVC, and then frozen at –18C for 4 months. GSE- and PG-containing samples retained their fresh cooked beef odor and flavor longer (p<0.05) than controls during storage. Rancid odor and flavor scores of GSE-containing samples were lower (p<0.05) than those of controls after 4 months of storage. The L* value of all samples increased (p<0.05) during storage. Thiobarbituric acid reactive substances (TBARS) of the control and AA-containing samples increased (p<0.05); those of GSE-containing samples did not change significantly (p>0.05) over the storage period.

Low spatial frequency filtering modulates early brain processing of affective complex pictures

Recent research on affective processing has suggested that low spatial frequency information of fearful faces provide rapid emotional cues to the amygdala, whereas high spatial frequencies convey fine-grained information to the fusiform gyrus, regardless of emotional expression. In the present experiment, we examined the effects of low (LSF, <15 cycles/image width) and high spatial frequency filtering (HSF, >25 cycles/image width) on brain processing of complex pictures depicting pleasant, unpleasant, and neutral scenes. Event-related potentials (ERP), percentage of recognized stimuli and response times were recorded in 19 healthy volunteers. Behavioral results indicated faster reaction times in response to unpleasant LSF than to unpleasant HSF pictures. Unpleasant LSF pictures and pleasant unfiltered pictures also elicited significant enhancements of P1 amplitudes at occipital electrodes as compared to neutral LSF and unfiltered pictures, respectively; whereas no significant effects of affective modulation were found for HSF pictures. Moreover, mean ERP amplitudes in the time between 200 and 500ms post-stimulus were significantly greater for affective (pleasant and unpleasant) than for neutral unfiltered pictures; whereas no significant affective modulation was found for HSF or LSF pictures at those latencies. The fact that affective LSF pictures elicited an enhancement of brain responses at early, but not at later latencies, suggests the existence of a rapid and preattentive neural mechanism for the processing of motivationally relevant stimuli, which could be driven by LSF cues. Our findings confirm thus previous results showing differences on brain processing of affective LSF and HSF faces, and extend these results to more complex and social affective pictures.

Image summarisation: human action description from static images

Dissertação de Mestrado, Processamento de Linguagem Natural e Indústrias da Língua, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2014

Effect of pre-treatments and post-treatments on drying products

Freeze drying technology can give good quality attributes of vegetables and fruits in terms of color, nutrition, volume, rehydration kinetics, stability during storage, among others, when compared with solely air dried ones. However, published scientific works showed that treatments applied before and after air dehydration are effective in food attributes, improving its quality. Therefore, the hypothesis of the present thesis was focus in a vast research of scientific work that showed the possibility to apply a pre-treatment and a post-treatment to food products combined with conventional air drying aiming being close, or even better, to the quality that a freeze dried product can give. Such attributes are the enzymatic inactivation, stability during storage, drying and rehydration kinetics, color, nutrition, volume and texture/structure. With regard to pre-treatments, the ones studied along the present work were: water blanching, steam blanching, ultrasound, freezing, high pressure and osmotic dehydration. High electric pulsed field was also studied but the food attributes were not explained on detailed. Basically, water and steam blanching showed to be adequate to inactivate enzymes in order to prevent enzymatic browning and preserve the product quality during long storage periods. With regard to ultrasound pre-treatment the published results pointed that ultrasound is an effective pre-treatment to reduce further drying times, improve rehydration kinetics and color retention. On the other hand, studies showed that ultrasound allow sugars losses and, in some cases, can lead to cell disruption. For freezing pre-treatment an overall conclusion was difficult to draw for some food attributes, since, each fruit or vegetable is unique and freezing comprises a lot of variables. However, for the studied cases, freezing showed to be a pre-treatment able to enhance rehydration kinetics and color attributes. High pressure pre-treatment showed to inactivate enzymes improving storage stability of food and showed to have a positive performance in terms of rehydration. For other attributes, when high pressure technology was applied, the literature showed divergent results according with the crops used. Finally, osmotic dehydration has been widely used in food processing to incorporate a desired salt or sugar present in aqueous solution into the cellular structure of food matrix (improvement of nutrition attribute). Moreover, osmotic dehydration lead to shorter drying times and the impregnation of solutes during osmose allow cellular strengthens of food. In case of post-treatments, puffing and a new technology denominated as instant controlled pressure drop (DIC) were reported in the literature as treatments able to improve diverse Abstract Effect of Pre-treatments and Post-treatments on Drying Products x food attributes. Basically, both technologies are similar where the product is submitted to a high pressure step and the process can make use of different heating mediums such as CO2, steam, air and N2. However, there exist a significant difference related with the final stage of both which can comprise the quality of the final product. On the other hand, puffing and DIC are used to expand cellular tissues improving the volume of food samples, helping in rehydration kinetics as posterior procedure, among others. The effectiveness of such pre and/or post-treatments is dependent on the state of the vegetables and fruits used which are also dependent of its cellular structure, variety, origin, state (fresh, ripe, raw), harvesting conditions, etc. In conclusion, as it was seen in the open literature, the application of pre-treatments and post-treatments coupled with a conventional air dehydration aim to give dehydrated food products with similar quality of freeze dried ones. Along the present Master thesis the experimental data was removed due to confidential reasons of the company Unilever R&D Vlaardingen

Dynamic Image Precompensation for Improving Visual Performance of Computer Users with Ocular Aberrations

With the progress of computer technology, computers are expected to be more intelligent in the interaction with humans, presenting information according to the user's psychological and physiological characteristics. However, computer users with visual problems may encounter difficulties on the perception of icons, menus, and other graphical information displayed on the screen, limiting the efficiency of their interaction with computers. In this dissertation, a personalized and dynamic image precompensation method was developed to improve the visual performance of the computer users with ocular aberrations. The precompensation was applied on the graphical targets before presenting them on the screen, aiming to counteract the visual blurring caused by the ocular aberration of the user's eye. A complete and systematic modeling approach to describe the retinal image formation of the computer user was presented, taking advantage of modeling tools, such as Zernike polynomials, wavefront aberration, Point Spread Function and Modulation Transfer Function. The ocular aberration of the computer user was originally measured by a wavefront aberrometer, as a reference for the precompensation model. The dynamic precompensation was generated based on the resized aberration, with the real-time pupil diameter monitored. The potential visual benefit of the dynamic precompensation method was explored through software simulation, with the aberration data from a real human subject. An "artificial eye'' experiment was conducted by simulating the human eye with a high-definition camera, providing objective evaluation to the image quality after precompensation. In addition, an empirical evaluation with 20 human participants was also designed and implemented, involving image recognition tests performed under a more realistic viewing environment of computer use. The statistical analysis results of the empirical experiment confirmed the effectiveness of the dynamic precompensation method, by showing significant improvement on the recognition accuracy. The merit and necessity of the dynamic precompensation were also substantiated by comparing it with the static precompensation. The visual benefit of the dynamic precompensation was further confirmed by the subjective assessments collected from the evaluation participants.

Enhancement of the total phenolic compounds and antioxidant activity of aqueous Citrus limon L. pomace extracts using microwave pre-treatment on the dry powder

The effect of microwave pre-treatment on the levels of total phenolic compounds, flavonoids, proanthocyanidins and individual major compounds as well as the total antioxidant activity of the dried lemon pomace was investigated. The results showed that microwave pre-treatment significantly affected all the examined parameters. The total phenolic content, total flavonoids, proanthocyanidins, as well as the total antioxidant activity significantly increased as the microwave radiation time and power increased (e.g., 2.5 folds for phenolics, 1.4 folds for flavonoids and 5.5 folds for proanthocyanidins), however irradiation more than 480 W for 5 min resulted in the decrease of these parameters. These findings indicate that microwave irradiation time and power may enhance higher levels of the phenolic compounds as well as the antioxidant capacity of the dried lemon pomace powder. However, higher and longer irradiation may lead to a degradation of phenolic compounds and lower the antioxidant capacity of the dried lemon pomace.

New methodologies in CT perfusion and MRI analysis to develop cancer imaging biomarkers

Quantitative imaging in oncology aims at developing imaging biomarkers for diagnosis and prediction of cancer aggressiveness and therapy response before any morphological change become visible. This Thesis exploits Computed Tomography perfusion (CTp) and multiparametric Magnetic Resonance Imaging (mpMRI) for investigating diverse cancer features on different organs. I developed a voxel-based image analysis methodology in CTp and extended its use to mpMRI, for performing precise and accurate analyses at single-voxel level. This is expected to improve reproducibility of measurements and cancer mechanisms’ comprehension and clinical interpretability. CTp has not entered the clinical routine yet, although its usefulness in the monitoring of cancer angiogenesis, due to different perfusion computing methods yielding unreproducible results. Instead, machine learning applications in mpMRI, useful to detect imaging features representative of cancer heterogeneity, are mostly limited to clinical research, because of results’ variability and difficult interpretability, which make clinicians not confident in clinical applications. In hepatic CTp, I investigated whether, and under what conditions, two widely adopted perfusion methods, Maximum Slope (MS) and Deconvolution (DV), could yield reproducible parameters. To this end, I developed signal processing methods to model the first pass kinetics and remove any numerical cause hampering the reproducibility. In mpMRI, I proposed a new approach to extract local first-order features, aiming at preserving spatial reference and making their interpretation easier. In CTp, I found out the cause of MS and DV non-reproducibility: MS and DV represent two different states of the system. Transport delays invalidate MS assumptions and, by correcting MS formulation, I have obtained the voxel-based equivalence of the two methods. In mpMRI, the developed predictive models allowed (i) detecting rectal cancers responding to neoadjuvant chemoradiation showing, at pre-therapy, sparse coarse subregions with altered density, and (ii) predicting clinically significant prostate cancers stemming from the disproportion between high- and low- diffusivity gland components.

Embedded systems and advanced signal processing for Acousto- Ultrasonic Inspections

Non Destructive Testing (NDT) and Structural Health Monitoring (SHM) are becoming essential in many application contexts, e.g. civil, industrial, aerospace etc., to reduce structures maintenance costs and improve safety. Conventional inspection methods typically exploit bulky and expensive instruments and rely on highly demanding signal processing techniques. The pressing need to overcome these limitations is the common thread that guided the work presented in this Thesis. In the first part, a scalable, low-cost and multi-sensors smart sensor network is introduced. The capability of this technology to carry out accurate modal analysis on structures undergoing flexural vibrations has been validated by means of two experimental campaigns. Then, the suitability of low-cost piezoelectric disks in modal analysis has been demonstrated. To enable the use of this kind of sensing technology in such non conventional applications, ad hoc data merging algorithms have been developed. In the second part, instead, imaging algorithms for Lamb waves inspection (namely DMAS and DS-DMAS) have been implemented and validated. Results show that DMAS outperforms the canonical Delay and Sum (DAS) approach in terms of image resolution and contrast. Similarly, DS-DMAS can achieve better results than both DMAS and DAS by suppressing artefacts and noise. To exploit the full potential of these procedures, accurate group velocity estimations are required. Thus, novel wavefield analysis tools that can address the estimation of the dispersion curves from SLDV acquisitions have been investigated. An image segmentation technique (called DRLSE) was exploited in the k-space to draw out the wavenumber profile. The DRLSE method was compared with compressive sensing methods to extract the group and phase velocity information. The validation, performed on three different carbon fibre plates, showed that the proposed solutions can accurately determine the wavenumber and velocities in polar coordinates at multiple excitation frequencies.

Content-aware approach for improving biomedical image analysis: an interdisciplinary study series

Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity.

Le radici del monoteismo israelitico come riflesso dell'idea di regalita divina in epoca pre-esilica

Questa tesi è un contributo al dibattito meta-terminologico sull'uso scientifico del termine "monoteismo" in relazione alla religione dell'Israele antico. L'attenzione è rivolta principalmente a un tema specifico: l'esplorazione della nozione teistica di "esistenza" divina (implicita nell'uso di "monoteismo" come lente di osservazione) e il problema della sua applicazione alle concettualizzazioni della divinità che emergono nella Bibbia ebraica. In primo luogo, il "monoteismo" come termine e concetto viene ricondotto alle sue origini storiche nell'ambiente intellettuale del platonismo di Cambridge nell'Inghilterra del XVII secolo. Poi, si affronta il dibattito contemporaneo sull'uso del termine "monoteismo" in relazione alla religione dell'Israele antico e si evidenzia il ruolo dell'"esistenza" teistica come lente distorcente nella lettura dei testi biblici. La maggior parte della tesi sostiene questo assunto con una lettura esegetica dettagliata di tre passi biblici scelti come casi di studio: Sal 82; 1Re 18,20-40* e Zc 14,9. Queste analisi mostrano come la nozione teistica di un'esistenza divina astratta non sia in grado di spiegare la rappresentazione del divino che emerge da questi testi. Allo stesso tempo, il potere divino come categoria euristica viene proposto come un'alternativa più adatta a spiegare queste concettualizzazioni della divinità. L'ultima sezione elabora ulteriormente questi risultati. Qui la regalità di YHWH, come immagine metaforica del suo potere, viene utilizzata per descrivere i cambiamenti nella concettualizzazione di questa divinità. L'argomentazione finale è che in nessuna parte del materiale biblico affrontato in questa tesi si trova una nozione simile a quella di esistenza divina astratta. Poiché tale nozione è implicita nell'uso del termine "monoteismo", questi risultati richiedono una considerazione ancora più attenta del suo uso nel dibattito scientifico.

Voice conversion with pre-trained representations for audio anonymization

The recording and processing of voice data raises increasing privacy concerns for users and service providers. One way to address these issues is to move processing on the edge device closer to the recording so that potentially identifiable information is not transmitted over the internet. However, this is often not possible due to hardware limitations. An interesting alternative is the development of voice anonymization techniques that remove individual speakers characteristics while preserving linguistic and acoustic information in the data. In this work, a state-of-the-art approach to sequence-to-sequence speech conversion, ini- tially based on x-vectors and bottleneck features for automatic speech recognition, is explored to disentangle the two acoustic information using different pre-trained speech and speakers representation. Furthermore, different strategies for selecting target speech representations are analyzed. Results on public datasets in terms of equal error rate and word error rate show that good privacy is achieved with limited impact on converted speech quality relative to the original method.

Antibody-Antigen Interface Characterization with Contextualized Pre-trained Embeddings

Artificial Intelligence (AI) has substantially influenced numerous disciplines in recent years. Biology, chemistry, and bioinformatics are among them, with significant advances in protein structure prediction, paratope prediction, protein-protein interactions (PPIs), and antibody-antigen interactions. Understanding PPIs is critical since they are responsible for practically everything living and have several uses in vaccines, cancer, immunology, and inflammatory illnesses. Machine Learning (ML) offers enormous potential for effectively simulating antibody-antigen interactions and improving in-silico optimization of therapeutic antibodies for desired features, including binding activity, stability, and low immunogenicity. This research looks at the use of AI algorithms to better understand antibody-antigen interactions, and it further expands and explains several difficulties encountered in the field. Furthermore, we contribute by presenting a method that outperforms existing state-of-the-art strategies in paratope prediction from sequence data.