Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Eating behavior and body image among psychology students

OBJECTIVE: To characterize eating habits and possible risk factors associated with eating disorders among psychology students, a segment at risk for eating disorders. METHOD: This is a cross-sectional study. The questionnaires Bulimic Investigatory Test Edinburgh (BITE), Eating Attitudes Test (EAT-26), Body Shape Questionnaire (BSQ) and a variety that considers related issues were applied. Statistical Package for the Social Sciences (SPSS) 11.0 was utilized in analysis. The study population was composed of 175 female students, with a mean age of 21.2 (DP ± 3.6 years). RESULTS: A positive result was detected on the EAT-26 for 6.9% of the cases (CI95%: 3.6-11.7%). The prevalence of increased symptoms and intense gravity, according to the BITE questionnaire was 5% (CI95%: 2.4-9.5%) and 2.5% (CI95%: 0.7-6.3%), respectively. According to the findings, 26.29% of the students presented abnormal eating behavior. The population with moderate/severe BSQ scores presented dissatisfaction with corporal weight. CONCLUSION: The results indicate that attention must be given to eating behavior risks within this group. A differentiated gaze is justified with respect to these future professionals, whose practice is jeopardized in cases in which they are themselves the bearers of installed symptoms or precursory behavior.

Body image dissatisfaction and its relationship with physical activity and body mass index in Brazilian adolescents

Objective: To evaluate body image dissatisfaction and its relationship with physical activity and body mass index in a Brazilian sample of adolescents. Methods: A total of 275 adolescents (139 boys and 136 girls) between the ages of 14 and 18 years completed measures of body image dissatisfaction through the Contour Drawing Scale and current physical activity by the International Physical Activity Questionnaire. Weight and height were also measured for subsequent calculation of body mass index. Results: Boys and girls differed significantly regarding body image dissatisfaction, with girls reporting higher levels of dissatisfaction. Underweight and eutrophic boys preferred to be heavier, while those overweight preferred be thinner and, in contrast, girls desired to be thinner even when they are of normal weight. Conclusion: Body image dissatisfaction was strictly related to body mass index, but not to physical activity.

Automating the testing process of image processing algorithms

As digital imaging processing techniques become increasingly used in a broad range of consumer applications, the critical need to evaluate algorithm performance has become recognised by developers as an area of vital importance. With digital image processing algorithms now playing a greater role in security and protection applications, it is of crucial importance that we are able to empirically study their performance. Apart from the field of biometrics little emphasis has been put on algorithm performance evaluation until now and where evaluation has taken place, it has been carried out in a somewhat cumbersome and unsystematic fashion, without any standardised approach. This paper presents a comprehensive testing methodology and framework aimed towards automating the evaluation of image processing algorithms. Ultimately, the test framework aims to shorten the algorithm development life cycle by helping to identify algorithm performance problems quickly and more efficiently.

Variations and application conditions of the data type "Image" : the foundation of computational visualistics

Visualistics, computer science, picture syntax, picture semantics, picture pragmatics, interactive pictures

Untersuchung der Laufradströmung einer Kreiselpumpe unter Teillastbedingungen mit Hilfe der particle image velocimetry

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2009

Hand gesture spotting and recognition using HMMs and CRFs in color image sequences

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2010

Vision-based representation and recognition of human activities in image sequences

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

Evaluierung und Entwicklung einer Image-Broschüre hinsichtlich industrieller Kooperationspartner für den Fachbereich Informatik und Kommunikationssysteme der Hochschule Merseburg

[s.c.]

Software phantoms in medical image analysis

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Instruments for image guided procedures - IIGP : review summaries for minimal invasive and image guided technologies and clinical procedures : student review papers on selected topics

Michael Friebe, editor ; Otto-von-Guericke-Universität Magdeburg, Institut für Medizintechnik, Lehrstuhl Kathetertechnologie und bildgesteuerte Therapie (INKA - Intelligente Katheter), Forschungscampus STIMULATE (Solution Centre for Image Guided Local Therapies)

Image registration techniques with multiresolution analysis in satellite oceanography

En aquest article es fa una descripció dels procediments realitzats per enregistrar dues imatges geomètricament, de forma automàtica, si es pren la primera com a imatge de referència. Es comparen els resultats obtinguts mitjançant tres mètodes. El primer mètode és el d’enregistrament clàssic en domini espacial maximitzant la correlació creuada (MCC)[1]. El segon mètode es basa en aplicar l’enregistrament MCC conjuntament amb un anàlisi multiescala a partir de transformades wavelet [2]. El tercer mètode és una variant de l’anterior que es situa a mig camí dels dos. Per cada un dels mètodes s’obté una estimació dels coeficients de la transformació que relaciona les dues imatges. A continuació es transforma per cada cas la segona imatge i es georeferencia respecte la primera. I per acabar es proposen unes mesures quantitatives que permeten discutir i comparar els resultats obtinguts amb cada mètode.