Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

Optimum-Path Forest pruning parameter estimation through Harmony Search

Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.

Substitution of corn and soybean oil by cassava meal and African palm tree oil in diets of laying hens

Fourty-two White Leghorns laying hens, from the commercial Cuban hybrid L-33, were used for eight weeks during the laying peak (36 to 43 weeks of age), to assess the substitution of corn by cassava root meal (Manihot esculenta Crantz) and the crude soybean oil by crude oil of African palm tree (Elaeis guineensis J.) in the diets of laying hens. Analysis of variance was conducted, according to simple classification design, with three treatments and 14 repetitions (a cage with a hen). The treatments consisted of three diets (1- corn meal + soybean oil; 2- 25 % cassava meal + African palm tree oil; 3- 53 % cassava meal + African palm tree oil), with 15.71 % CP; 3.83 % Ca and 0.36 % P available. The viability was of 100 % in all treatments. No differences were found for laying (92.21, 92.09 and 91.59 %), which surpassed the potential of this hybrid during the laying peak (90 %), conversion (118g feedstuff/egg in the three treatments), egg mass produced (3066, 3114 and 3071 g/bird) and mass conversion (1.99, 1.95 y 1.98 feed consumed/egg mass). The pigmentation of the egg yolk was reduced as the level of cassava meal increased in the diets (6, 4 and 3 at Roche's scale), as well as the cost of the feed consumed in 56 d per hen (2.56, 2.15 and 1.83 USD/bird). The possibility of substituting, totally, corn meal by that of cassava and soybean oil by that of the African palm tree in the diets of laying hens during the laying peak was determined, with positive economic effect and without damaging the productive performance of birds.

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.

Statistical analysis of texture in trunk images for biometric identification of tree species

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

Dormancy breaking of the fig tree with hydrogen cyanamide and garlic extrate

The supply of cold hours needed to the dormancy breaking of shoots is the limiting factor for the cultivation of temperate climate fruit trees in warmer regions. In subtropical conditions, it is necessary to use chemical products to promote uniform sprouting. This research aimed at evaluating the effect of garlic extract and hydrogen cyanamide in sprouting, growth, production and production cycle of the fig tree. The experiment was conducted during the production cycles of 2011/12 and 2012/13. We used plants from the cultivar Roxo de Valinhos. Production pruning was made in the months of July/2011 and July/2012, and the following treatments were applied immediately after it: 2% hydrogen cyanamide and garlic extract in 4%, 8% and 12% doses, and a control treatment. Split plots were used as the experimental design, with five repetitions in blocks; each plot consisted of five treatments with hydrogen cyanamide, garlic extract and control; the subplots consisted of two production cycles. The use of hydrogen cyanamide promoted an anticipation of sprouting and the use of hydrogen cyanamide and garlic extract promoted a concentration of the productive period, when compared to the control. The estimated garlic extract dose that promoted the highest production per plant was 3%.

Carbohydrates, growth and production of -roxo de valinhos- fig tree in initial development under irrigation management

The carbohydrates translocation and consequently growth and production of fig tree (Ficuscarica L.) vary according to the different management on cultivation conditions. The aim of this study was to evaluate the changes in the levels and total carbohydrates accumulation together with growth and “Roxo de Valinhos” fig trees production onimplementation of orchards in initial phase, cultivated with and without irrigation. We adopted a factorial arrangement (2 x 7) with four repetitions distributed in installments (with and without irrigation) subdivided in time (collect time). Destructive analyzes were performed at 40, 80, 120, 160, 200, 240 and 280 days after pruning (DAP) and are measured: stem diameter and branch, stem length and branch, number of leaves, internodes and fruit. Subsequently, the plant parts were sectioned to obtain the leaf area, length and roots volume, fresh and dry matter weight. The number, weight and total productivity of fruits were evaluated. The media of all growth attributes and production characteristics were higher in treatments with water irrigation. The total carbohydrate content was higher at 120 and 160 DAP and the carbohydrates accumulation was increasing for most institutions over the plants development, except for the leaves that showed a decrease in the levels at 160 DAP. The fruits showed greater carbohydrates accumulation in relation to the other evaluated organs.