Volume Estimation of Small Particles Using Three-Dimensional Reconstruction from Multiple Views

Castillo-Castañeda, Eduardo; Turchiuli, Christelle

doi:10.1007/978-3-540-69905-7_25

Cited by 10 publications

(10 citation statements)

References 8 publications

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“…In real applicative scenarios, the measurement accuracy of three-dimensional reconstruction methods can be drastically reduced due to occlusions, noise, dust, and segmentation errors. For this reason, it should be necessary to adopt robust segmentation techniques [22] and specifically designed measurement methods [23][24][25].…”

Section: Resultsmentioning

confidence: 99%

A virtual environment for the simulation of 3D wood strands in multiple view systems for the particle size measurements

Labati

Genovese

Piuri

et al. 2013

2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applicati

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In this paper, we present a complete virtual environment for the computation of synthetic three-dimensional samples representing free falling wood strands.The proposed method permits to simulate acquisitions performed by real multiple view setups in which the stream of strands falling out of a conveyor belt is analyzed with image processing techniques in order to compute the particle size distribution. Unfortunately, experiments in real time applications are complex and expensive, and the ground true is almost impossible to measure in such conditions. The creation of a metric and fully virtual environment of falling wood strands represent a key feature in order to properly design the illuminotecnic and optical setups, optimize the image processing methods as well as the three-dimensional reconstruction techniques, using controlled and fully repeatable virtual image datasets.The implemented method first computes realistic threedimensional models of wood strands with known shape characteristics. Then, the strands are rotated and translated into a global three-dimensional space. Finally, realistic effects are applied and images related to different viewpoints are computed.Experimental results show that the realized virtual environment can effectively be used for the simulation of multiple view acquisitions, obtaining realistic synthetic samples and effectively allowing designing and test image processing algorithms.

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Section: Resultsmentioning

confidence: 99%

A virtual environment for the simulation of 3D wood strands in multiple view systems for the particle size measurements

Labati

Genovese

Piuri

et al. 2013

2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applicati

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“…SFS techniques are usually adopted when the objects that should be measured can be moved and complex setups can be employed. Examples of applications are the archaeological vessels [10,11], or off-line analyses of irregularly-shaped objects [2].…”

Section: Previous Workmentioning

confidence: 99%

Low-cost volume estimation by two-view acquisitions: A computational intelligence approach

Labati

Genovese

Piuri

et al. 2012

The 2012 International Joint Conference on Neural Networks (IJCNN)

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The estimation of the volume occupied by an object is an important task in the fields of granulometry, quality control, and archaeology. An accurate and well know technique for the volume measurement is based on the Archimedes' principle. However, in many applications it is not possible to use this technique and faster contact-less techniques based on image processing or laser scanning should be adopted.In this work, we propose a low-cost approach for the volume estimation of different kinds of objects by using a two-view vision approach. The method first computes a reduced threedimensional model from a single couple of images, then extracts a series of features from the obtained model. Lastly, the features are processed using a computational intelligence approach, which is able to learn the relation between the features and the volume of the captured object, in order to estimate the volume independently of its position and angle, and without computing a full three-dimensional model.Results show that the approach is feasible and can obtain an accurate volume estimation. Compared to the direct computation of the volume from the three-dimensional models, the approach is more accurate and also less dependent to the position and angle of the measured objects with respect to the cameras.

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“…The object will be immersed in liquid and the displacement will be measured, but the product may be damaged during the process. This method is inaccurate, especially for fragile or porous objects [3,4]. The gas displacement method preserves the condition of the food and leaves it intact, but it is not suitable for a fast measurement system.…”

Section: Introductionmentioning

confidence: 99%

In-Line Sorting of Harumanis Mango Based on External Quality Using Visible Imaging

Ibrahim

Saad

Zakaria

et al. 2016

Sensors

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The conventional method of grading Harumanis mango is time-consuming, costly and affected by human bias. In this research, an in-line system was developed to classify Harumanis mango using computer vision. The system was able to identify the irregularity of mango shape and its estimated mass. A group of images of mangoes of different size and shape was used as database set. Some important features such as length, height, centroid and parameter were extracted from each image. Fourier descriptor and size-shape parameters were used to describe the mango shape while the disk method was used to estimate the mass of the mango. Four features have been selected by stepwise discriminant analysis which was effective in sorting regular and misshapen mango. The volume from water displacement method was compared with the volume estimated by image processing using paired t-test and Bland-Altman method. The result between both measurements was not significantly different (P > 0.05). The average correct classification for shape classification was 98% for a training set composed of 180 mangoes. The data was validated with another testing set consist of 140 mangoes which have the success rate of 92%. The same set was used for evaluating the performance of mass estimation. The average success rate of the classification for grading based on its mass was 94%. The results indicate that the in-line sorting system using machine vision has a great potential in automatic fruit sorting according to its shape and mass.

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Volume Estimation of Small Particles Using Three-Dimensional Reconstruction from Multiple Views

Cited by 10 publications

References 8 publications

A virtual environment for the simulation of 3D wood strands in multiple view systems for the particle size measurements

A virtual environment for the simulation of 3D wood strands in multiple view systems for the particle size measurements

Low-cost volume estimation by two-view acquisitions: A computational intelligence approach

In-Line Sorting of Harumanis Mango Based on External Quality Using Visible Imaging

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