A MICRO-IMAGE FUSION ALGORITHM BASED ON REGION GROWING

Due to the limitation of Depth Of Field (DOF) of microscope, the regions which are not within the DOF will be blurring after imaging. Thus for micro-image fusion, the most important step is to identify the blurring regions within each micro-image, so as to remove their undesirable impacts on the fused image. In this paper, a fusion algorithm based on a novel region growing method is proposed for micro-image fusion. The local sharpness of micro-image is judged block by block, then blocks whose sharpness is lower than an adaptive threshold are used as seeds, and the sharpness of neighbors of each seed are evaluated again during the region growing until the blurring regions are identified completely. With the decreasing in block size, the obtained region segmentation becomes more and more accurate. Finally, the micro-images are fused with pixel-wise fusion rules. The experimental results show that the proposed algorithm benefits from the novel region segmentation and it is able to obtain fused micro-image with higher sharpness compared with some popular image fusion method.

The application of near-infrared spectra micro-image in the imaging analysis of biology samples

In this research,suitable imaging methods were used for acquiring single compound images ofbiology samples of chicken pectorales tissue section,tobacco dry leaf,fresh leaf and plantglandular hair,respectively.The adverse effects caused by the high water content and thethermal effect of near infrared(NIR)light were effectively solved during the experiment procedures and the data procesing.PCA algorithm was applied to the NIR micro-image of chickenpectorales tissue.Comparing the loading vector of PC3 with the NIR spectrum of dry albumen,the information of PC3 was confimmed to be provided mainly by protein,i.e.,the 3rd score imagerepresents the distribution trend of protein mainly.PCA algorithm was applied to the NIR micro-image of tobacco dry leaf.The information of PC2 was confimed to be provided by carbohydrateindluding starch mainly.Compared to the 2nd score image of tobacco dry leaf,the comparedcorelation image with the reference spectrum of starch had the same distribution trend as the 2nd score image.The comparative correla tion images with the reference spectra of protein,glucose,fructose and the total plant alkaloid were acquired to confirm the distribution trend ofthese compounds in tobacco dry leaf respectively.Comparative correlation images of fresh leafwith the reference spectra of protein,starch,fructose,ghucose and water were acquired to confim the distribution trend of these compounds in fresh leaf.Chemimap imaging of plant glandularhair was acquired to show the tubular structure clearly.

Modeling yarn-level geometry from a single micro-image

Different types of cloth show distinctive appearances owing to their unique yarn-level geometrical details.Despite its importance in applications such as cloth rendering and simulation,capturing yarn-level geometry is nontrivial and requires special hardware,e.g.,computed tomography scanners,for conventional methods.In this paper,we propose a novel method that can produce the yarn-level geometry of real cloth using a single micro-image,captured by a consumer digital camera with a macro lens.Given a single input image,our method estimates the large-scale yarn geometry by image shading,and the fine-scale fiber details can be recovered via the proposed fiber tracing and generation algorithms.Experimental results indicate that our method can capture the detailed yarn-level geometry of a wide range of cloth and reproduce plausible cloth appearances.

A log-based method for fine-scale evaluation of lithofacies and its applications to the Gulong shale in the Songliao Basin,Northeast China

The Gulong shale demonstrates high clay content and pronounced thin laminations,with limited vertical variability in log curves,complicating lithofacies classification.To comprehend the distribution and compositional features of lithofacies in the Gulong shale for optimal sweet spot selection and reservoir stimulation,this study introduced a lithofacies classification scheme and a log-based lithofacies evaluation method.Specifically,theΔlgR method was utilized for accurately determining the total organic carbon(TOC)content;a multi-mineral model based on element-to-mineral content conversion coefficients was developed to enhance mineral composition prediction accuracy,and the microresistivity curve variations derived from formation micro-image(FMI)log were used to compute lamination density,offering insights into sedimentary structures.Using this method,integrating TOC content,sedimentary structures,and mineral compositions,the Qingshankou Formation is classified into four lithofacies and 12 sublithofacies,displaying 90.6%accuracy compared to core description outcomes.The classification results reveal that the northern portion of the study area exhibits more prevalent fissile felsic shales,siltstone interlayers,shell limestones,and dolomites.Vertically,the upper section primarily exhibits organic-rich felsic shale and siltstone interlayers,the middle part is characterized by moderate organic quartz-feldspathic shale and siltstone/carbonate interlayers,and the lower section predominantly features organic-rich fissile felsic/clayey felsic shales.Analyzing various sublithofacies in relation to seven petrophysical parameters,oil test production,and fracturing operation conditions indicates that the organic-rich felsic shales in the upper section and the organic-rich/clayey felsic shales in the lower section possess superior physical properties and oil content,contributing to smoother fracturing operation and enhanced production,thus emerging as dominant sublithofacies.Conversely,thin interlayers such as siltstones and limestones,while producing oil,demonstrate higher brittleness and pose great fracturing operation challenges.The methodology and insights in this study will provide a valuable guide for sweet spot identification and horizontal well-based exploitation of the Gulong shale.

Visualization of CO_2 and oil immiscible and miscible flow processes in porous media using NMR micro-imaging

CO2 flooding is considered not only one of the most effective enhanced oil recovery （EOR） methods, but also an important alternative for geological CO2 storage. In this paper, the visualization of CO2 flooding was studied using a 400 MHz NMR micro-imaging system. For gaseous CO2 immiscible displacement, it was found that CO2 channeling or fingering occurred due to the difference of fluid viscosity and density. Thus, the sweep efficiency was small and the final residual oil saturation was 53.1%. For supercritical CO2 miscible displacement, the results showed that piston-like displacement occurred, viscous fingering and the gravity override caused by the low viscosity and density of the gas was effectively restrained, and the velocity of CO2 front was uniform. The sweep efficiency was so high that the final residual oil saturation was 33.9%, which indicated CO2 miscible displacement could enhance oil recovery more than CO2 immiscible displacement. In addition, the average velocity of CO2 front was evaluated through analyzing the oil saturation profile. A special core analysis method has been applied to in-situ oil saturation data to directly evaluate the local Darcy phase velocities and capillary dispersion rate.

Analysis Microstructure of Weld Metal for HQ130+QJ63 High Strength Steel

The microstructure in the weld metals for HQ130 + QJ63 high strength steels,which are welded by Ar-CO_2 gas shielded metal arc welding,was analyzed by means of microscope and scan electron microscope(SEM).The relative content of different microstructure was evaluated with XQF-2000 micro-image analyzer.The effect of acicular ferrite content on the impact toughness was also studied.The test results indicated that the main microstructure in the weld metals of HQ130 + QJ63 high strength steels is acicular ferrite and a few pro-eutectic ferrite on the boundary of original austenite grain.Near the fusion zone there are columnar grains whose direction coefficient(X) is 3.22,but the microstructure in the center of the weld metal is isometric grain,whose direction coefficient X = 1.In order to avoid welding crack and improve welding technology the weld heat input should be strictly controlled in 10-16 kJ/cm.Thus,the main microstructure in the weld metals is fine acicular ferrite and the content of pro-eutectic ferrite is limited.The impact toughness in the weld metals of HQ130+ QJ63 steels can be ensured and can meet the requirements for application in engineering and machinery.

Study on a New Technique of On-line Monitoring of Oil Contamination Level Using Computer Vision Technology

In this paper, a new technique of capturing the images of debris inlubrication or hydraulic oil using micro-imaging and computer vision techniques is introduced. Byway of image processing, the size and distribution of debris are obtained, and then the oilcontamination level is also obtained. Because the information of oil contamination is obtaineddirectly from the images of debris by this method, the monitoring result is more intuitive andreliable.

Study of spatial distribution for the active ingredient in ibuprofen tablet based on near-infrared micro-imaging technology

The NIR micro-images of ibuprofen tablets were collected in this research.Compare correlation imaging and principal component analysis（PC A） with histogram were applied to acquire the spatial distribution of ibuprofen granule.The result indicated that a similar distribution trend can be acquired by both of the two methods mentioned above;the information of PC2 results from ibuprofen mainly since the correlation coefficient between PC2 loading vector and the NIR spectrum of ibuprofen is 0.9930.The result of PCA indicated that the information of PC2 results from ibuprofen mainly for both the low and the high content of ibuprofen in the tablets.The correlation coefficient between the data of the two PC2 loading vectors of the low and the high content of ibuprofen in the tablets is 0.9998,which indicates that the result of PCA is stable and reliable.