Optical-electronic system for express analysis of mineral raw materials dressability by color sorting method

Alekhin, Artem A.; Gorbunova, Elena V.; Chertov, Aleksandr N.; Petuhova, Darya B.

doi:10.1117/12.2020460

Cited by 7 publications

(2 citation statements)

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“…The described algorithm is used in the development of electro-optical system for express analysis of mineral raw materials dressability by color sorting method [7]. It can also be the basis for the development of software for new more intelligent optical sorters of solid minerals.…”

Section: Discussionmentioning

confidence: 99%

Principles of image processing in machine vision systems for the color analysis of minerals

et al. 2014

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At the moment color sorting method is one of promising methods of mineral raw materials enrichment. This method is based on registration of color differences between images of analyzed objects. As is generally known the problem with delimitation of close color tints when sorting low-contrast minerals is one of the main disadvantages of color sorting method. It is can be related with wrong choice of a color model and incomplete image processing in machine vision system for realizing color sorting algorithm. Another problem is a necessity of image processing features reconfiguration when changing the type of analyzed minerals. This is due to the fact that optical properties of mineral samples vary from one mineral deposit to another. Therefore searching for values of image processing features is non-trivial task. And this task doesn't always have an acceptable solution. In addition there are no uniform guidelines for determining criteria of mineral samples separation. It is assumed that the process of image processing features reconfiguration had to be made by machine learning. But in practice it's carried out by adjusting the operating parameters which are satisfactory for one specific enrichment task. This approach usually leads to the fact that machine vision system unable to estimate rapidly the concentration rate of analyzed mineral ore by using color sorting method. This paper presents the results of research aimed at addressing mentioned shortcomings in image processing organization for machine vision systems which are used to color sorting of mineral samples. The principles of color analysis for low-contrast minerals by using machine vision systems are also studied. In addition, a special processing algorithm for color images of mineral samples is developed. Mentioned algorithm allows you to determine automatically the criteria of mineral samples separation based on an analysis of representative mineral samples. Experimental studies of the proposed algorithm were performed using samples of gold and copper-nickel ores. And obtained results confirmed its efficiency with respect to mineral objects. The research results will allow: expanding the use of the color sorting method in the field of mineral raw materials enrichment; facilitating the search for values of image processing features for machine vision systems which are used to the color analysis of minerals; reducing the time required for reconfiguration of image processing features when changing the type of analyzed minerals; realizing the process of rapid estimating the concentration rate of analyzed mineral ore by using color sorting method.

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Section: Discussionmentioning

confidence: 99%

Principles of image processing in machine vision systems for the color analysis of minerals

et al. 2014

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“…Sensor-based sorting provides solutions for sorting various products, for instance according to quality aspects [1]. Typical fields of application are found in food processing [2], [3], recycling [4], [5], and handling of industrial minerals [6], [7]. In many cases, a sorting task aims at separating low-quality objects from high-quality objects and hence results in an accept or reject task.…”

Section: Introductionmentioning

confidence: 99%

Fast multitarget tracking via strategy switching for sensor-based sorting

Maier

Pfaff

Pieper

et al. 2016

2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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State-of-the-art sensor-based sorting systems provide solutions to sort various products according to quality aspects. Such systems face the challenge of an existing delay between perception and separation of the material. To reliably predict an object’s position when reaching the separation stage, information regarding its movement needs to be derived. Multitarget tracking offers approaches through which this can be achieved. However, processing time is typically limited since the sorting decision for each object needs to be derived sufficiently early before it reaches the separation stage. In this paper, an approach for multitarget tracking in sensor-based sorting is proposed which supports establishing an upper bound regarding processing time required for solving the measurement to track association problem. To demonstrate the success of the proposed method, experiments are conducted for datasets obtained via simulation of a sorting system. This way, it is possible to not only demonstrate the impact on required runtime but also on the quality of the association

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Simulation of multicomponent light source for optical-electronic system of color analysis objects

2016

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Optical-electronic system for express analysis of mineral raw materials dressability by color sorting method

Cited by 7 publications

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Principles of image processing in machine vision systems for the color analysis of minerals

Principles of image processing in machine vision systems for the color analysis of minerals

Fast multitarget tracking via strategy switching for sensor-based sorting

Simulation of multicomponent light source for optical-electronic system of color analysis objects

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