The determination of the content of impurities is a very frequent analysis performed on virgin olive oil samples, but the official method is quite work-intensive, and it would be convenient to have an alternative appr...
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The determination of the content of impurities is a very frequent analysis performed on virgin olive oil samples, but the official method is quite work-intensive, and it would be convenient to have an alternative approximate method to evaluate the performance of the impurity removal process. In this work we develop a system based on computervision and patternrecognition to classify the content of impurities of the olive oil samples in three sets, indicative of the goodness of the separation process of olive oil after its extraction from the paste. Starting from the histograms of the channels of the Red-Green-Blue (RGB), CIELAB and Hue-Saturation-Value (HSV) color spaces, we construct an initial input parameter vector and perform a feature extraction previous to the classification. Several linear and non-linear feature extraction techniques were evaluated, and the classifiers used were Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs). The best classification rate achieved was 87.66%, obtained using Kernel Principal Components Analysis (KPCA) and a grade-3-polynomial kernel SVM. The best result using ANNs was 82.38%, yielded by the use of Principal Component Analysis (PCA) with the Perceptron. (C) 2013 Elsevier Ltd. All rights reserved.
Recently, variational relaxation techniques for approximating solutions of partitioning problems on continuous image domains have received considerable attention, since they introduce significantly less artifacts than...
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Recently, variational relaxation techniques for approximating solutions of partitioning problems on continuous image domains have received considerable attention, since they introduce significantly less artifacts than established graph cut-based techniques. This work is concerned with the sources of such artifacts. We discuss the importance of differentiating between artifacts caused by discretization and those caused by relaxation and provide supporting numerical examples. Moreover, we consider in depth the consequences of a recent theoretical result concerning the optimality of solutions obtained using a particular relaxation method. Since the employed regularizer is quite tight, the considered relaxation generally involves a large computational cost. We propose a method to significantly reduce these costs in a fully automatic way for a large class of metrics including tree metrics, thus generalizing a method recently proposed by Strekalovskiy and Cremers (IEEE conference on computervision and patternrecognition, pp. 1905-1911, 2011).
Cotton, as one of the four major economic crops, is of great significance to the development of the national economy. Monitoring cotton growth status by automatic image-based detection makes sense due to its low-cost,...
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ISBN:
(纸本)9780819498069
Cotton, as one of the four major economic crops, is of great significance to the development of the national economy. Monitoring cotton growth status by automatic image-based detection makes sense due to its low-cost, low-labor and the capability of continuous observations. However, little research has been done to improve close observation of different growth stages of field crops using digital cameras. Therefore, algorithms proposed by us were developed to detect the growth information and predict the starting date of cotton automatically. In this paper, we introduce an approach for automatic detecting five true-leaves stage, which is a critical growth stage of cotton. On account of the drawbacks caused by illumination and the complex background, we cannot use the global coverage as the unique standard of judgment. Consequently, we propose a new method to determine the five true-leaves stage through detecting the node number between the main stem and the side stems, based on the agricultural meteorological observation specification. The error of the results between the predicted starting date with the proposed algorithm and artificial observations is restricted to no more than one day.
This volume constitutes the refereed proceedings of the 5th Iberian Conference on patternrecognition and Image Analysis, IbPRIA 2011, held in Las Palmas de Gran Canaria, Spain, in June 2011. The 34 revised full paper...
ISBN:
(纸本)9783642386299
This volume constitutes the refereed proceedings of the 5th Iberian Conference on patternrecognition and Image Analysis, IbPRIA 2011, held in Las Palmas de Gran Canaria, Spain, in June 2011. The 34 revised full papers and 58 revised poster papers presented were carefully reviewed and selected from 158 submissions. The papers are organized in topical sections on computervision; image processing and analysis; medical applications; and patternrecognition.
Given 3-D sensor data of points slightly moving in space, we consider the problem of discerning whether or not translation, rotation, and scale change take place and to what extent. For this purpose, we propose a new ...
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Given 3-D sensor data of points slightly moving in space, we consider the problem of discerning whether or not translation, rotation, and scale change take place and to what extent. For this purpose, we propose a new method for fitting various motion models to 3-D sensor data. Based on the observation that subgroups of 3-D affinity are defined by imposing various internal constraints on the parameters, our method fits 3-D affinity with internal constraints using the scheme of EFNS, which, unlike conventional methods, dispenses with any particular parameterizations for particular motion models. Then, we apply our method to simulated stereo vision data for motion interpretation, using various model selection criteria. We also apply our method to the GPS geodetic data of the land deformation in northeast Japan, where a massive earthquake took place on 11 March 2011. It is expected that our proposed technique will be widely used for 3-D analysis involving hierarchical motion models in various domains including computervision, robotic navigation, and geodetic science. (C) 2012 Elsevier Ltd. All rights reserved.
As iris recognition systems have been deployed in many security areas, liveness detection that can distinguish between real iris patterns and fake ones becomes an important module. Most existing algorithms focus on th...
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ISBN:
(纸本)9781467350532;9781467350525
As iris recognition systems have been deployed in many security areas, liveness detection that can distinguish between real iris patterns and fake ones becomes an important module. Most existing algorithms focus on the appearance difference between real and fake iris (for example, printed patterns, cosmetic contact lenses etc.) which is a very difficult problem. Instead of studying image properties of fake irises, we show that pupil constriction, the fundamental characteristic of real and live irises, can be very robust for liveness detection. In this experimental study, we first build an iris acquisition system that can acquire two eye images under two different illumination conditions in a less intrusive environment. Second, in order to model the process of pupil constriction, we propose a feature descriptor that consists of similarity measurement between iris patches and ratio of iris and pupil diameters. Third, the performance of liveness prediction is evaluated based on the training of a Support Vector Machine (SVM) classifier. The high success prediction rate shows that the classifier is effective without knowing any prior knowledge of fake irises.
vision is an extremely important sense for both humans and robots, providing detailed information about the environment. In the past few years, the use of digital cameras in robotic applications has been increasing si...
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This special issue of Journal of Mathematical Imaging and vision contains expanded versions of papers presented at Sibgrapi 2011, the 24th Conference on Graphics, patterns, and Images. Sibgrapi is the most traditional...
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This special issue of Journal of Mathematical Imaging and vision contains expanded versions of papers presented at Sibgrapi 2011, the 24th Conference on Graphics, patterns, and Images. Sibgrapi is the most traditional meeting in Latin America on computer Graphics, Image Processing, patternrecognition and computervision.
Autonomous robots are becoming an integrated part of our daily life. The use of a robot for substituting man power in different activities that might be too dangerous, repetitive or time consuming, has become a common...
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