Fractal descriptors for discrimination of microscopy images of plant leaves

This study proposes the application of fractal descriptors method to the discrimination of microscopy images of plant leaves. Fractal descriptors have demonstrated to be a powerful discriminative method in image analysis, mainly for the discrimination of natural objects. In fact, these descriptors express the spatial arrangement of pixels inside the texture under different scales and such arrangements are directly related to physical properties inherent to the material depicted in the image. Here, we employ the Bouligand-Minkowski descriptors. These are obtained by the dilation of a surface mapping the gray-level texture. The classification of the microscopy images is performed by the well-known Support Vector Machine (SVM) method and we compare the success rate with other literature texture analysis methods. The proposed method achieved a correctness rate of 89%, while the second best solution, the Co-occurrence descriptors, yielded only 78%. This clear advantage of fractal descriptors demonstrates the potential of such approach in the analysis of the plant microscopy images.

Deriving vegetation indices for phenology analysis using genetic programming

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

Should phylogenetic and functional diversity metrics compose macroinvertebrate multimetric indices for stream biomonitoring?

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

Automatic method to classify images based on multiscale fractal descriptors and paraconsistent logic

In this study is presented an automatic method to classify images from fractal descriptors as decision rules, such as multiscale fractal dimension and lacunarity. The proposed methodology was divided in three steps: quantification of the regions of interest with fractal dimension and lacunarity, techniques under a multiscale approach; definition of reference patterns, which are the limits of each studied group; and, classification of each group, considering the combination of the reference patterns with signals maximization (an approach commonly considered in paraconsistent logic). The proposed method was used to classify histological prostatic images, aiming the diagnostic of prostate cancer. The accuracy levels were important, overcoming those obtained with Support Vector Machine (SVM) and Bestfirst Decicion Tree (BFTree) classifiers. The proposed approach allows recognize and classify patterns, offering the advantage of giving comprehensive results to the specialists.

Mass and surface fractal in supercritical dried silica aerogels prepared with additions of sodium dodecyl sulfate

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

Plant identification based on leaf midrib cross-section images using fractal descriptors

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

The taxonomic distinctness of macroinvertebrate communities of Atlantic Forest streams cannot be predicted by landscape and climate variables, but traditional biodiversity indices can

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

Can geometric indices of heart rate variability predict improvement in autonomic modulation after resistance training in chronic obstructive pulmonary disease?

Chronic obstructive pulmonary disease (COPD) is associated with autonomic dysfunctions that can be evaluated through heart rate variability (HRV). Resistance training promotes improvement in autonomic modulation; however, studies that evaluate this scenario using geometric indices, which include nonlinear evaluation, thus providing more accurate information for physiological interpretation of HRV, are unknown. This study aimed to investigate the influence of resistance training on autonomic modulation, using geometric indices of HRV, and peripheral muscle strength in individuals with COPD. Fourteen volunteers with COPD were submitted to resistance training consisting of 24 sessions lasting 60 min each, with a frequency of three times a week. The intensity was determined as 60% of one maximum repetition and was progressively increased until 80% for the upper and lower limbs. The HRV and dynamometry were performed at two moments, the beginning and the end of the experimental protocol. Significant increases were observed in the RRtri (4·81 ± 1·60 versus 6·55 ± 2·69, P = 0·033), TINN (65·36 ± 35·49 versus 101·07 ± 63·34, P = 0·028), SD1 (7·48 ± 3·17 versus 11·04 ± 6·45, P = 0·038) and SD2 (22·30 ± 8·56 versus 32·92 ± 18·78, P = 0·022) indices after the resistance training. Visual analysis of the Poincare plot demonstrated greater dispersion beat-to-beat and in the long-term interval between consecutive heart beats. Regarding muscle strength, there was a significant increase in the shoulder abduction and knee flexion. In conclusion, geometric indices of HRV can predict improvement in autonomic modulation after resistance training in individuals with COPD; improvement in peripheral muscle strength in patients with COPD was also observed.

Aplicações médicas das abordagens complexas não lineares: a geometria fractal do EEG

Pós-graduação em Saúde Coletiva - FMB

Indices de vegetação na mensuração do estoque de carbono em áreas com cana-de-açúcar

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Color texture analysis based on fractal descriptors

Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods. (C) 2011 Elsevier Ltd. All rights reserved.

Fractal descriptors based on Fourier spectrum applied to texture analysis

This work proposes the development and study of a novel technique lot the generation of fractal descriptors used in texture analysis. The novel descriptors are obtained from a multiscale transform applied to the Fourier technique of fractal dimension calculus. The power spectrum of the Fourier transform of the image is plotted against the frequency in a log-log scale and a multiscale transform is applied to this curve. The obtained values are taken as the fractal descriptors of the image. The validation of the proposal is performed by the use of the descriptors for the classification of a dataset of texture images whose real classes are previously known. The classification precision is compared to other fractal descriptors known in the literature. The results confirm the efficiency of the proposed method. (C) 2012 Elsevier B.V. All rights reserved.

Shape analysis using fractal dimension: A curvature based approach

The present work shows a novel fractal dimension method for shape analysis. The proposed technique extracts descriptors from a shape by applying a multi-scale approach to the calculus of the fractal dimension. The fractal dimension is estimated by applying the curvature scale-space technique to the original shape. By applying a multi-scale transform to the calculus, we obtain a set of descriptors which is capable of describing the shape under investigation with high precision. We validate the computed descriptors in a classification process. The results demonstrate that the novel technique provides highly reliable descriptors, confirming the efficiency of the proposed method. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4757226]

Probing the anomalous extinction of four young star clusters: the use of colour-excess, main-sequence fitting and fractal analysis

Aims. We studied four young star clusters to characterise their anomalous extinction or variable reddening and asses whether they could be due to contamination by either dense clouds or circumstellar effects. Methods. We evaluated the extinction law (R-V) by adopting two methods: (i) the use of theoretical expressions based on the colour-excess of stars with known spectral type; and (ii) the analysis of two-colour diagrams, where the slope of the observed colour distribution was compared to the normal distribution. An algorithm to reproduce the zero-age main-sequence (ZAMS) reddened colours was developed to derive the average visual extinction (A(V)) that provides the closest fit to the observational data. The structure of the clouds was evaluated by means of a statistical fractal analysis, designed to compare their geometric structure with the spatial distribution of the cluster members. Results. The cluster NGC 6530 is the only object of our sample affected by anomalous extinction. On average, the other clusters suffer normal extinction, but several of their members, mainly in NGC 2264, seem to have high R-V, probably because of circumstellar effects. The ZAMS fitting provides A(V) values that are in good agreement with those found in the literature. The fractal analysis shows that NGC 6530 has a centrally concentrated distribution of stars that differs from the substructures found in the density distribution of the cloud projected in the A(V) map, suggesting that the original cloud was changed by the cluster formation. However, the fractal dimension and statistical parameters of Berkeley 86, NGC 2244, and NGC 2264 indicate that there is a good cloud-cluster correlation, when compared to other works based on an artificial distribution of points.

Electromyographic indices, orofacial myofunctional status and temporomandibular disorders severity: A correlation study

This study examined whether there is an association between surface electromyography (EMG) of masticatory muscles, orofacial myofunction status and temporomandibular disorder (TMD) severity scores. Forty-two women with TMD (mean 30 years, SD 8) and 18 healthy women (mean 26 years, SD 6) were examined. According to the Research Diagnostic Criteria for TMD (RDC/TMD), all patients had myogenous disorders plus disk displacements with reduction. Surface EMG of masseter and temporal muscles was performed during maximum teeth clenching either on cotton rolls or in intercuspal position. Standardized EMG indices were obtained. Validated protocols were used to determine the perception severity of TMD and to assess orofacial myofunctional status. TMD patients showed more asymmetry between right and left muscle pairs, and more unbalanced contractile activities of contralateral masseter and temporal muscles (p < 0.05, t-test), worse orofacial myofunction status and higher TMD severity scores (p < 0.05, Mann-Whitney test) than healthy subjects. Spearman coefficient revealed significant correlations between EMG indices, orofacial myofunctional status and TMD severity (p < 0.05). In conclusion, these methods will provide useful information for TMD diagnosis and future therapeutic planning. (C) 2011 Elsevier Ltd. All rights reserved.