Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Texture analysis by multi-resolution fractal descriptors

This work proposes a novel texture descriptor based on fractal theory. The method is based on the Bouligand- Minkowski descriptors. We decompose the original image recursively into four equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The proposed descriptors are provided by concatenating such measures. The method is tested in a classification experiment under well known datasets, that is, Brodatz and Vistex. The results demonstrate that the novel technique achieves better results than classical and state-of-the-art texture descriptors, such as Local Binary Patterns, Gabor-wavelets and co-occurrence matrix.

Combining fractal and deterministic walkers for texture analysis and classification

In this paper,we present a novel texture analysis method based on deterministic partially self-avoiding walks and fractal dimension theory. After finding the attractors of the image (set of pixels) using deterministic partially self-avoiding walks, they are dilated in direction to the whole image by adding pixels according to their relevance. The relevance of each pixel is calculated as the shortest path between the pixel and the pixels that belongs to the attractors. The proposed texture analysis method is demonstrated to outperform popular and state-of-the-art methods (e.g. Fourier descriptors, occurrence matrix, Gabor filter and local binary patterns) as well as deterministic tourist walk method and recent fractal methods using well-known texture image datasets.

Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.

Exploring the use of local binary patterns as focus measure

[EN]In this work local binary patterns based focus measures are presented. Local binary patterns (LBP) have been introduced in computer vision tasks like texture classification or face recognition. In applications where recognition is based on LBP, a computational saving can be achieved with the use of LBP in the focus measures. The behavior of the proposed measures is studied to test if they fulfill the properties of the focus measures and then a comparison with some well know focus measures is carried out in different scenarios.

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.

Soil Influence on Forest Vegetation Productivity and Patterns in the Eastern Cascades of Southern Oregon

Thesis (Master's)--University of Washington, 2016-06

Shading and texture:Separate information channels with a common adaptation mechanism?

We outline a scheme for the way in which early vision may handle information about shading (luminance modulation, LM) and texture (contrast modulation, CM). Previous work on the detection of gratings has found no sub-threshold summation, and no cross-adaptation, between LM and CM patterns. This strongly implied separate channels for the detection of LM and CM structure. However, we now report experiments in which adapting to LM (or CM) gratings creates tilt aftereffects of similar magnitude on both LM and CM test gratings, and reduces the perceived strength (modulation depth) of LM and CM gratings to a similar extent. This transfer of aftereffects between LM and CM might suggest a second stage of processing at which LM and CM information is integrated. The nature of this integration, however, is unclear and several simple predictions are not fulfilled. Firstly, one might expect the integration stage to lose identity information about whether the pattern was LM or CM. We show instead that the identity of barely detectable LM and CM patterns is not lost. Secondly, when LM and CM gratings are combined in-phase or out-of-phase we find no evidence for cancellation, nor for 'phase-blindness'. These results suggest that information about LM and CM is not pooled or merged - shading is not confused with texture variation. We suggest that LM and CM signals are carried by separate channels, but they share a common adaptation mechanism that accounts for the almost complete transfer of perceptual aftereffects.

Patterns of rare earth and other trace elements in Paleogene and Miocene clayey sediments from the Mondego platform (Central Portugal)

In the present study the origin of clay deposits occurring in an inland platform, in central Portugal, was investigated by their mineralogical and chemical composition. The clay deposits, exploited for ceramic industry are composed of silt-clay facies, the Monteira Member and the Arroça Member, which are assigned to the Coja Formation (Paleogene) and the Campelo Formation (Miocene), respectively. These clayey facies show almost compositional homogeneity, especially concerning texture. The mineralogical composition of the Monteira Member displays slightly higher content in smectite and interstratified clay minerals, which is supported by the chemical composition of samples analyzed. Both members present similar REE patterns, displaying an intense weathering record and little variation in the source area composition. Minor element geochemistry suggests low content in heavy minerals and transition metals. REE patterns and ratios of geochemical parameters support the dominant metasedimentary provenance, with a granite source contribution and also mature recycled sediments of continental origin. The study results’ suggest that the clays of these two members have the same source in terms of lithology and recycled sediments from the Hesperian massif. During the deposition of the Arroça Member, a major remobilization of the Monteira Member is suggested, explaining the geochemical similarity of both facies.

Characterization Of Cumulative Joint Damage Patterns In Patients With Rheumatoid Arthritis: A Clinical, Serological, And Gene Polymorphism Perspective.

To characterize cumulative joint damage (CJD) patterns in rheumatoid arthritis (RA) and determine their associations with demographic/clinical features and HLA-DRB1 gene polymorphism. Hand and foot radiographs were obtained from 404 patients with RA. CJD patterns were determined by 3 derivations from Sharp/van der Heijde scores, obtained by the mathematical division of scores for hands/feet (Sharp-h/f score), fingers/wrists (Sharp-f/w score), and erosion/space narrowing (Sharp-e/sn score), respectively. DNA and serum were obtained for determination of HLA-DRB1 polymorphism, rheumatoid factor (RF), and anticitrullinated protein antibodies (ACPA). Patients with wrist-dominant CJD pattern were more likely to have severe RA than those with finger-dominant pattern (68.4% vs 46.0%; p = 0.036) as were those with foot-dominant vs hand-dominant CJD pattern (76.5% vs 56.4%; p = 0.044). HLA-DRB1 shared epitope (SE) alleles were associated with erosion-dominant CJD pattern (p = 0.021). Patients with erosion-dominant CJD pattern had higher levels of RF and ACPA than those with space-narrowing-dominant CJD pattern (median RF 71.35 U/ml vs 22.05 U/ml, respectively; p = 0.003; median ACPA 187.9 U/ml vs 143.2 U/ml, respectively; p < 0.001). The majority of triple-positive patients (SE+, RF+, ACPA+) had erosion-dominant CJD pattern (62.3%) while the majority of triple-negative patients (SE-, FR-, ACPA-) had space narrowing-dominant CJD pattern (75%; p = 0.017). ACPA was associated with HLA-DRB1 SE alleles (p < 0.05). Patients with foot-dominant CJD pattern were taller than those with hand-dominant CJD pattern (p = 0.002); those with erosion-dominant CJD pattern had higher weight and body mass index than those with space narrowing-dominant CJD pattern (p = 0.014, p = 0.001). CJD patterns were associated with disease severity, HLA-DRB1 SE status, presence and titer of ACPA and RF, and morphometric features.

Environmental Controls In The Water Use Patterns Of A Tropical Cloud Forest Tree Species, Drimys Brasiliensis (winteraceae).

Trees from tropical montane cloud forest (TMCF) display very dynamic patterns of water use. They are capable of downwards water transport towards the soil during leaf-wetting events, likely a consequence of foliar water uptake (FWU), as well as high rates of night-time transpiration (Enight) during drier nights. These two processes might represent important sources of water losses and gains to the plant, but little is known about the environmental factors controlling these water fluxes. We evaluated how contrasting atmospheric and soil water conditions control diurnal, nocturnal and seasonal dynamics of sap flow in Drimys brasiliensis (Miers), a common Neotropical cloud forest species. We monitored the seasonal variation of soil water content, micrometeorological conditions and sap flow of D. brasiliensis trees in the field during wet and dry seasons. We also conducted a greenhouse experiment exposing D. brasiliensis saplings under contrasting soil water conditions to deuterium-labelled fog water. We found that during the night D. brasiliensis possesses heightened stomatal sensitivity to soil drought and vapour pressure deficit, which reduces night-time water loss. Leaf-wetting events had a strong suppressive effect on tree transpiration (E). Foliar water uptake increased in magnitude with drier soil and during longer leaf-wetting events. The difference between diurnal and nocturnal stomatal behaviour in D. brasiliensis could be attributed to an optimization of carbon gain when leaves are dry, as well as minimization of nocturnal water loss. The leaf-wetting events on the other hand seem important to D. brasiliensis water balance, especially during soil droughts, both by suppressing tree transpiration (E) and as a small additional water supply through FWU. Our results suggest that decreases in leaf-wetting events in TMCF might increase D. brasiliensis water loss and decrease its water gains, which could compromise its ecophysiological performance and survival during dry periods.

Patterns Of Seizure Control In Patients With Mesial Temporal Lobe Epilepsy With And Without Hippocampus Sclerosis.

Objective Patients with mesial temporal lobe epilepsy (MTLE) may present unstable pattern of seizures. We aimed to evaluate the occurrence of relapse-remitting seizures in MTLE with (MTLE-HS) and without (MTLE-NL) hippocampal sclerosis. Method We evaluated 172 patients with MTLE-HS (122) or MTLE-NL (50). Relapse-remitting pattern was defined as periods longer than two years of seizure-freedom intercalated with seizure recurrence. Infrequent seizures was considered as up to three seizures per year and frequent seizures as any period of seizures higher than that. Results Thirty-seven (30%) MTLE-HS and 18 (36%) MTLE-NL patients had relapse-remitting pattern (X2, p = 0.470). This was more common in those with infrequent seizures (X2, p < 0.001). Twelve MTLE-HS and one MTLE-NL patients had prolonged seizure remission between the first and second decade of life (X2, p = 0.06). Conclusion Similar proportion of MTLE-HS or MTLE-NL patients present relapse-remitting seizures and this occurs more often in those with infrequent seizures.

Breastfeeding and non-nutritive sucking patterns related to the prevalence of anterior open bite in primary dentition

OBJECTIVE: Nutritional, immunological and psychological benefts of exclusive breastfeeding for the frst 6 months of life are unequivocally recognized. However, mothers should also be aware of the importance of breastfeeding for promoting adequate oral development. This study evaluated the association between breastfeeding and non-nutritive sucking patterns and the prevalence of anterior open bite in primary dentition. MATERIAL AND METHODS: Infant feeding and non-nutritive sucking were investigated in a 3-6 year-old sample of 1,377 children, from São Paulo city, Brazil. Children were grouped according to breastfeeding duration: G1 - non-breastfed, G2 - shorter than 6 months, G3 - interruption between 6 and 12 months, and G4 - longer than 12 months. Three calibrated dentists performed clinical examinations and classifed overbite into 3 categories: normal, anterior open bite and deep bite. Chi-square tests (p<0.05) with odds ratio (OR) calculation were used for intergroup comparisons. The impact of breastfeeding and non-nutritive sucking on the prevalence of anterior open bite was analyzed using binary logistic regression. RESULTS: The prevalence estimates of anterior open bite were: 31.9% (G1), 26.1% (G2), 22.1% (G3), and 6.2% (G4). G1 would have signifcantly more chances of having anterior open bite compared with G4; in the total sample (OR=7.1) and in the subgroup without history of non-nutritive sucking (OR=9.3). Prolonging breastfeeding for 12 months was associated with a 3.7 times lower chance of having anterior open bite. In each year of persistence with non-nutritive sucking habits, the chance of developing this malocclusion increased in 2.38 times. CONCLUSIONS: Breastfeeding and non-nutritive sucking durations demonstrated opposite effects on the prediction of anterior open bite. Non-breastfed children presented signifcantly greater chances of having anterior open bite compared with those who were breastfed for periods longer than 12 months, demonstrating the benefcial infuence of breastfeeding on dental occlusion.

Polyamine patterns in haploid and diploid tobacco tissues and in vitro cultures

The aim of this work was to determine PAs levels in pith tissues and callus cultures from haploid and diploid tobacco plants, explanted from the apical and basal regions of the stem. These explants were cultured in an RM-64 medium supplied with IAA and kinetin, under light or in the dark, during successive subcultures. PAs levels followed a basipetal decrease in diploid and an increase in haploid, pith tissues. A similar pattern of total PAs (free + conjugated) was observed for the callus of diploid and haploid plants maintained in the light, and for the haploid callus in the dark, whereas the diploid callus in the dark showed a constant increase in total PAs levels until the end of culture. The PA increase in the diploid callus in the dark was related to free Put levels increase. The ploidy status of the plants could express different PA gradients together with the plant pith and in vitro callus cultures.