III. Image Processing Method of System. Image is the information transfer carrier of machine vision measuring system, and the quality of its original information obtained and advantage of image processing algorithm will directly influence the system performance. Therefore, in order to realize highprecision automatic measuring to the workpiece ...
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To test our object_ script, just issue the following command: python object_ image images/example_ width Your output should look something like the following: Figure 2: Measuring the size of objects in an image using OpenCV, Python, and computer vision + image processing techniques.
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By image processing, Yang [12] measured the particle size distribution of lump coal with a size range of ∼ 20 mm, and compared the statistical distribution with fractal distribution function and artificial sieving results, providing a novel and effective method for the particle size distribution measurement in the study of coal failure ...
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This review is based on how to measure particle sizes with different image processing techniques. In addition to this, particle size significantly affects the mechanical properties of the...
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Abstract nearest neighbour algorithm, and convex shell method to achieve preliminary segmentation, merge small pieces with large pieces, and split adhered particles, respectively. Comparing the automated segmentation using this method with manual segmentation, it is found that the results are comparable.
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To validate the feasibility of simultaneously measuring the size and velocity of coal powder by trajectory imaging, about 2000 coal particles with a size range of 100125 μm were recorded under the exposure time of 2 ms, and imaging magnification β= The obtained size and velocity were compared with that using the shadow image method ...
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The platform is composed of five modules, including module of coal seam and fault, module of laneway aided design and analysis, module of general ground surface situation and working condition, module of auxiliary view and layer managements, and module of dynamic visualization (an independent system). Download : Download fullsize image;
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In this paper, an image analysis method using MATLAB is proposed to measure fragment size distribution of coal fragments. The acquisition setup, analysis step and coding process for fragment size distribution measurement by digital imaging processing are introduced in detail.
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Two hundred images of coal piles comprised of coal sized above 3 mm were captured. Over 100 kg of coal were sampled and sieved manually into five size fractions: 36, 613, 1325, 2550, and 50100 mm. The size of the image was 1024 × 768 pixels and the imaged area was 18 × cm.
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Currently, there is little research on realtime monitoring methods for coal dry screening. Liao [] developed a new online automatic optical inspection system (OAOIS) applying digital image processing to measure the coarse particle size [] demonstrated the inconsistencies of lengthbased separation by mechanical sieving using standard sieves and developed a user ...
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Laser particle analyzer and image analysis were used to measure the particle size distribution of 6 coal samples with the size range of 1 ∼ 2 mm. Based on obtaining the size distribution, the average diameter was calculated. Then the diffusion coefficient was calculated by using the average diameter obtained by different methods.
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Size distribution measurement of coal fragments using digital imaging processing Xiaohan Yang a b, Ting Ren a b, Lihai Tan a Add to Mendeley https://// Get rights and content • Accurate and fast measurement of coal fragments generated by uniaxial compression tests using digital imaging processing. •
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An improved mass model with only two parameters for coarse coal particles using image analysis was established. ... and morphology have been analyzed qualitatively (Zhang et al., 2012a). With continued research on particles, particle size measurements based on quantitative methods have been proposed, and the shape, size and surface structure of ...
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Coal is heterogeneous in nature, and thus the characterization of coal is essential before its use for a specific purpose. Thus, the current study aims to develop a machine vision system for automated coal characterizations. The model was calibrated using 80 image samples that are captured for different coal samples in different angles. All the images were captured in RGB color space and ...
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Experimental results show that the combined high speed imaging and image processing technique has provided an effective means for measuring and quantifying the characteristics of single coal ...
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The existing and urgent problem to be solved is the low accuracy and efficiency of coal/gangue recognition. Image processing method is the most promising approach for automatic coal/gangue recognition [6], [7], [8]. However, because gangue is the blackgray solid wastes that mixed in coal, the main existing problems for imaging recognition is ...
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Meas. Sci. Technol. 20 (2009) 114006 HWanget al Nomenclature A matrix relating the 3D temperature in the furnace and temperature image a, b, c coefficients in the polynomial functions for calibration (/)B matrix used to reconstruct the 3D temperature distribution D matrix for regularization e relative difference (%) I spectral radiation intensity (W m −2 μm 1) R, G red and green data of ...
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The measurement accuracy of the particle size of coal determined by using he image acquisition and analysis system described in Section was verified by randomly selecting five particles in each size interval and measuring their sizes by the method outlined in Fig. 8.
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Besides analyzing the coal, a coal quality manager system should automatically calculate: Heating Value (kcal/kg, kJ/kg or BTU/lb) Lbs SO2 per million BTU. Volatile Matter. Fixed Carbon. Ash Fusion Temperature (based on customer specific empirical relations) Knowing these measurements in realtime enables coal producers to control sorting and ...
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Two image processing procedures were developed to ... respirable coal mine dust; particle size; mineral composition 1. Introduction In the coal mining industry, respirable coal mine dust (RCMD) is generated during ... Two 6 26 mm pieces were cut from each sample. One piece was cut from the edge, and the other piece was from near the center of ...
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Traditional grain size determination in materials characterization involves microscopy images and a laborious process requiring significant manual input and human expertise. In recent years, the development of computer vision (CV) has provided an alternative approach to microstructural characterization with preliminary implementations greatly simplifying the grain size determination process ...
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Online intelligent recognition of coal and gangue is an important aspect of coal mine intelligent development. Current research focuses more on improving recognition accuracy through optimizing image processing algorithms, but there is limited research on the characteristics of coal gangue materials themselves, particularly the comparative analysis of their appearance in images under different ...
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The noncontact digital image processing technology determines the deformation of the sample according to the deformation amount of the image taken when the coal deforms. Using computer to collect and process data is a noncontact and noninterfering deformation measurement technology that does not interfere with the deformation of the sample.
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To obtain the geometrical statistics of the coal cleat network at the core scale, quantitative image analysis methods on the segmented microCT images have been developed. BossieCodreanu et al. (2004) and ( Mazumder et al., 2006) measured cleat density, spacing, orientations and aperture sizes using microCT scanning.
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Particle size is an important physicochemical parameter of coal. The accurate measurement of particle size distribution (PSD) of coal samples is significant to both scientific research and engineering, such as coal combustion [15], coal chemical industry [69], adsorption and desorption [1012], and coal and gas outburst [13, 14].
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A quantitative analysis of the porosity, pore size distribution, and fractal dimensions of pores is significant for studying the pore structure characteristics of coal. This study utilized 12 anthracite coal samples from the Sihe mining area to explore the pore structure characteristics of the coal therein. Hundred randomly selected points on each sliced coal sample were imaged via scanning ...
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Abstract We developed an imaging technique for inspecting the inside of coalfired boilers during operation by using a visiblelight camera, which has a higher spatial resolution and depth of field than midinfrared image sensor camera systems commonly used for imaging the inside of boilers. Two main problems are associated with the use of a visiblelight camera: the low light transmittance of ...
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The pore wall thickness measurement by image analysis provided significant correlations with M 40, CRI and CSR values. This explains the usability of image analysis for coke structure measurement. A comparative study was carried out for measurement by volumetric method, image analysis, mercury porosimetry and Xray CT scan measurements.
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The pore structure parameters of coal have an important influence on the exploration and development of coalbed methane. In this study, a series of pore structure parameters, including porosity, pore radius, pore throat radius, pore coordination number, pore throat ratio, and specific surface area, are identified, extracted, and calculated in the scanning electron microscopy (SEM) images of ...
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Image matching is an important topic in image processing. Matching technology plays an important role in and is the basis for image understanding. In order to solve the shortcomings of slow image matching and low matching accuracy, a matching method based on improved genetic algorithm is proposed. The main improvement of the algorithm is the use of selfidentifying crossover operators for ...
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