IAACS: Image aesthetic assessment through color composition and space formation

Background Determining how an image is visually appealing is a complicated and subjective task. This motivates the use of a machine-learning model to evaluate image aesthetics automatically by matching the aesthetics of the general public. Although deep learning methods have successfully learned good visual features from images,correctly assessing the aesthetic quality of an image remains a challenge for deep learning. Methods To address this, we propose a novel multiview convolutional neural network to assess image aesthetics assessment through color composition and space formation(IAACS). Specifically, from different views of an image––including its key color components and their contributions, the image space formation, and the image itself––our network extracts the corresponding features through our proposed feature extraction module(FET) and the Image Net weight-based classification model. Result By fusing the extracted features, our network produces an accurate prediction score distribution for image aesthetics. The experimental results show that we have achieved superior performance.

Pre-processing for time domain image formation in SS-BSAR system

A pre-processing procedure is designed for a space-surface bistatic synthetic aperture radar （SS-BSAR） system when a time domain image formation algorithm is employed. Three crucial technical issues relating to the procedure are fully discussed. Firstly, unlike image formation algorithms operating in the frequency domain, a time domain algorithm requires the accurate global navigation satellite system （GNSS） time and position. This paper proposes acquisition of this information using a time-and-spatial transfer with precise ephemeris and interpolation. Secondly, synchronization errors and compensation methods in SS-BSAR are analyzed. Finally, taking the non-ideal factors in the echo and the compatibility of image formation algorithms into account, a matched filter based on the minimum delay is constructed. Experimental result using real data suggest the pre-processing is functioning properly.

Wave Optics and Image Formation in Gravitational Lensing

We investigate image formations in gravitational lensing systems using wave optics. Applying the Fresnel-Kirchhoff diffraction formula to waves scattered by a gravitational potential of a lens object, we demonstrate how images of source objects are obtained directly from wave functions without using a lens equation for gravitational lensing. As an example of image formation in gravitational lensing, images of a point source by a point mass gravitational lens are presented. These images reduce to those obtained by a ray tracing method in the geometric optics limit.

Modeling Camera Image Formation Using a Feedforward Neural Network

One fundamental problem in computer vision and image processing is modeling the image formation of a camera, i.e., mapping a point in three-dimensional space to its projected position on the camera’s image plane. If the relationship between the space and the image plane is assumed to be linear, the relationship can be expressed in terms of a transfor-mation matrix and the matrix is often identified by regression. In this paper, we show that the space-to-image relation-ship in a camera can be modeled by a simple neural network. Unlike most other cases employing neural networks, the structure of the network is optimized so as for each link between neurons to have a physical meaning. This makes it possible to effectively initialize link weights and quickly train the network.

Imaging-Based Characterization of Perthite in the Upper Triassic Yanchang Formation Tight Sandstone of the Ordos Basin,China

This work investigated the element distribution of perthite from the Upper Triassic Yanchang Formation tight sandstone in the Ordos Basin of northern China by field emission scanning electron microscopy(FE-SEM) and energy dispersive spectrometer(EDS). FE-SEM results indicate significant differences in the morphology of Na-rich feldspar when K-rich feldspar is the main component of the perthite. EDS results show that different types of perthite have clearly defined differences on different element indexes. Additionally, indexes such as average-weight-K(K-rich)/Na(Na-rich), maximumweight-K(Na-rich)/Na(Na-rich) and average-atomic-K(K-rich)/Na(Na-rich) might be the most effective ones to identify perthite types. Perthite is divided into six main types, i.e., perthite with thick parallel stripe distribution, with thin parallel stripe distribution, with lumpy stripe distribution, with dendritic stripe distribution, with encircling stripe distribution, and with mixed stripe distribution.

Iris Liveness Detection Using Fragmental Energy of Haar Transformed Iris Images Using Ensemble of Machine Learning Classifiers

Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses,replayed the video,and print attacks.The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness.Seven assorted feature creation ways are studied in the presented solutions,and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.The predicted iris liveness identification variants are evaluated using recall,F-measure,precision,accuracy,APCER,BPCER,and ACER.Three standard datasets were used in the investigation.The main contribution of our study is achieving a good accuracy of 99.18%with a smaller feature vector.The fragmental coefficients of Haar transformed iris image of size 8∗8 utilizing random forest algorithm showed superior iris liveness detection with reduced featured vector size(64 features).Random forest gave 99.18%accuracy.Additionally,conduct an extensive experiment on cross datasets for detailed analysis.The results of our experiments showthat the iris biometric template is decreased in size tomake the proposed framework suitable for algorithmic verification in real-time environments and settings.

Discoloration Range and Shroud Image Depth Values Cannot Be Satisfied by the Same Proton Energy

The radiative hypothesis has been revisited showing other characteristics, produced by the protons used as dyes in total disagree with the ones of the Body Image that appears on the Shroud of Turin. Our investigations highlight that for the protons to reach 3.7 cm in air, the distance that measures the range of discoloration effects, must be emitted with an energy of about 1.5 MeV using Wilson and Brobeck’s empirical formula and 1.35 MeV using Bethe’s. This last formula provides a result closer to reality. Bethe shows that the penetration depth is greater than that calculated empirically. Such a value of proton energy (1.35 MeV) makes it possible to satisfy the discoloration effects range for the Shroud but it is incompatible with a depth of penetration in linen that is only 200 nm. Moreover, using the same subatomic particles, we obtained on the colored linen a distribution of energy represented by regression but not linear. Thus, also the possible I(z) correlation, between color intensity and body-sheet distance, which should be due to the oxidizing action of protons, does not agree with that extracted from the Shroud of Turin.

基于ImageJ的图片格式批量转换软件的设计与实现

介绍了开源的纯Java语言图像处理程序——ImageJ,以及如何利用ImageJ程序包进行二次开发。利用该程序包,实现了从WinView所获取的图片文件格式TIFF、SPE到FITS文件格式的批量转换。并在此基础上,提出了如何利用该程序包实现其它图片格式之间相互单独以及批量转换的方法。

Bedding parallel fractures in fine-grained sedimentary rocks:Recognition,formation mechanisms,and prediction using well log

Core,thin section,conventional and image logs are used to provide insights into distribution of fractures in fine grained sedimentary rocks of Permian Lucaogou Formation in Jimusar Sag.Bedding parallel fractures are common in fine grained sedimentary rocks which are characterized by layered structures.Core and thin section analysis reveal that fractures in Lucaogou Formation include tectonic inclined fracture,bedding parallel fracture,and abnormal high pressure fracture.Bedding parallel fractures are abundant,but only minor amounts of them remain open,and most of them are partly to fully sealed by carbonate minerals(calcite)and bitumen.Bedding parallel fractures result in a rapid decrease in resistivity,and they are recognized on image logs to extend along bedding planes and have discontinuous surfaces due to partly-fully filled resistive carbonate minerals as well as late stage dissolution.A comprehensive interpretation of distribution of bedding parallel fractures is performed with green line,red line,yellow line and blue line representing bedding planes,induced fractures,resistive fractures,and open(bedding and inclined)fractures,respectively.The strike of bedding parallel fractures is coinciding with bedding planes.Bedding parallel fractures are closely associated with the amounts of bedding planes,and high density of bedding planes favor the formation of bedding parallel fractures.Alternating dark and bright layers have the most abundant bedding parallel fractures on the image logs,and the bedding parallel fractures are always associated with low resistivity zones.The results above may help optimize sweet spots in fine grained sedimentary rocks,and improve future fracturing design and optimize well spacing.

Prediction of multiscale laminae structure and reservoir quality in fine-grained sedimentary rocks:The Permian Lucaogou Formation in Jimusar Sag,Junggar Basin

Fine-grained sedimentary rocks have become a research focus as important reservoirs and source rocks for tight and shale oil and gas.Laminae development determines the accumulation and production of tight and shale oil and gas in fine-grained rocks.However,due to the resolution limit of conventional logs,it is challenging to recognize the features of centimeter-scale laminae.To close this gap,complementary studies,including core observation,thin section,X-ray diffraction(XRD),conventional log analysis,and slabs of image logs,were conducted to unravel the centimeter-scale laminae.The laminae recognition models were built using well logs.The fine-grained rocks can be divided into laminated rocks(lamina thickness of<0.01 m),layered rocks(0.01-0.1 m),and massive rocks(no layer or layer spacing of>0.1 m)according to the laminae scale from core observations.According to the mineral superposition assemblages from thin-section observations,the laminated rocks can be further divided into binary,ternary,and multiple structures.The typical mineral components,slabs,and T2spectrum distributions of various lamina types are unraveled.The core can identify the centimeter-millimeter-scale laminae,and the thin section can identify the millimeter-micrometer-scale laminae.Furthermore,they can detect mineral types and their superposition sequence.Conventional logs can identify the meter-scale layers,whereas image logs and related slabs can identify the laminae variations at millimeter-centimeter scales.Therefore,the slab of image logs combined with thin sections can identify laminae assemblage characteristics,including the thickness and vertical assemblage.The identification and classification of lamina structure of various scales on a single well can be predicted using conventional logs,image logs,and slabs combined with thin sections.The layered rocks have better reservoir quality and oil-bearing potential than the massive and laminated rocks.The laminated rocks’binary lamina is better than the ternary and multiple layers due to the high content of felsic minerals.The abovementioned results build the prediction model for multiscale laminae structure using well logs,helping sweet spots prediction in the Permian Lucaogou Formation in the Jimusar Sag and fine-grained sedimentary rocks worldwide.

A new laboratory method for evaluating formation damage in fractured carbonate reservoirs

Natural carbonate core samples with artificial fractures are often used to evaluate the damage of fractured carbonate formations in the laboratory. It is shown that the most frequent error for evaluation results directly from the random width characterized by the artificial fractures. To solve this problem, a series of simulated fractured core samples made of stainless steel with a given width of fracture were prepared. The relative error for the width of artificial fracture decreased to 1%. The width of natural and artificial fractures in carbonate reservoirs can be estimated by image log data. A series of tests for formation damage were conducted by using the stainless steel simulated core samples flushed with different drilling fluids, such as the sulfonate/polymer drill-in fluid and the solids-flee drill-in fluid with or without ideal packing bridging materials. Based on the experimental results using this kind of simulated cores, a novel approach to the damage control of fractured carbonate reservoirs was presented. The effective temporary plugging ring on the end face of the simulated core sample can be observed clearly. The experimental results also show that the stainless steel simulated cores made it possible to visualize the solids and filtrate invasion.

Eagle-Vision-Based Object Detection Method for UAV Formation in Hazy Weather

Inspired by eagle’s visual system,an eagle-vision-based object detection method for unmanned aerial vehicle(UAV)formation in hazy weather is proposed in this paper.To restore the hazy image,the values of atmospheric light and transmission are estimated on the basis of the signal processing mechanism of ON and OFF channels in eagle’s retina.Local features of the dehazed image are calculated according to the color antagonism mechanism and contrast sensitivity function of eagle’s visual system.A center-surround operation is performed to simulate the response of reception field.The final saliency map is generated by the Random Forest algorithm.Experimental results verify that the proposed method is capable to detect UAVs in hazy image and has superior performance over traditional methods.

Three-Dimensional Measurement and Reconstruction of Fabric Drape Shape

This paper introduces a new method of measuring the three-dimensional drape shape of fabrics with structural light. First, we apply parallel annular structural light to form light and shade alternating contour stripes on the surface of fabrics. We then collect the images of contour stripes using Charge Coupled Device (CCD). Subsequently, we process the images to identify the contour stripes and edges of fabrics, and obtain the fabric contour lines of curved surfaces. Finally, we apply three-dimensional curved surface modeling method based on a network of polar coordinates, and reconstruct the three-dimensional drape shape of fabrics. Experiments show that our method is effective in testing and reconstructing three-dimensional drape shape of fabrics.

SPS格式文件在I/O Image系统中的应用

SPS格式在I/O Image系统中的应用,有效地提高了生产效率。文中首先介绍了SPS格式的组成,然后详细地介绍了SPS文件在I/O Image系统中的制作、导入、导出方法,最后介绍了SPS格式在特殊采集方法下和复杂地区的应用以及使用过程中的野值问题。

An Eco-translatological Perspective on Shenzhen's International City Image Construction:Public Signs Translation as an Example

After the 26th Universiade,Shenzhen has been striving to build a balanced and harmonious translational eco-environment,and make Public Signs translation play a positive role in the construction of international city image.Meanwhile,Shenzhen has formed relative completed systems in beforehand prevention and subsequent punishment in public signs translation.However,there is also a long way to go to perfect the translation eco-environment construction.

Digitization and DICOM Standardization of X-ray Image Signal

Picture archiving and communication system (PACS) has played an important role in hospital and developed rapidly in recent years. It is an important part of PACS architecture that X-ray video output connects with PACS. In this paper, a method to digitize the video signals of X-ray facility is introduced. By means of the video capture card, we can acquire digital medical images from X-ray facility. The American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) developed a standard for Digital Imaging and Communications in Medicine (DICOM), this DICOM standard introduces a rule of medical image conversion from conventional format to DICOM one. According to abovementioned standard, X-ray video signals can be connected to PACS easily. This project has been applied in some hospitals successfully and there is satisfied result. Key words image acquisition - image compression - format conversion - DICOM - PACS CLC number TP 391 Foundation item: Supported by the Enterprise Innovation Foundation of Wuhan (WS(2001)14)Biography: ZHOU Li (1977-), male, Master, research direction: microelectronics and solid electronics.

Petrophysical Evaluation of a Severely Heterogeneous Carbonate Reservoir;Electrical Image Logs Usage in Porosity Estimation

Image logs have higher resolution than conventional logs and it makes them powerful tools for detailed reservoir characterization and modeling. Hence, thin beds, which are not detectable using conventional logs, can be characterized by image log data. The present study focuses on the Permian-Triassic carbonate reservoirs of Dalan and Kangan formations in one of the gas fields in southern Iran. In this study, the reservoir porosity was estimated using Fullbore Formation Microimager (FMI) image log. Then, the results were compared and validated with the core data. Porosity was estimated as 2-dimentional image by rescaling the FMI image log with Micro-Spherical Focused Log (MSFL). The image log-derived porosity was then compared with conventional logs-derived and core porosities. The image log-derived porosity is in good agreement with the core data. In this paper, a procedure was introduced which can be used to recognize very narrow pay layers (thickness in centimeters). This work is very important for identifying the proper perforation intervals in heterogeneous reservoirs.

AUTOMATIC SEGMENTATION OF HIPPOCAMPAL SUBFIELDS BASED ON MULTI-ATLAS IMAGE SEGMENTATION TECHNIQUES

The volume of hippocampal subfields is closely related with early diagnosis of Alzheimer's disease.Due to the anatomical complexity of hippocampal subfields,automatic segmentation merely on the content of MR images is extremely difficult.We presented a method which combines multi-atlas image segmentation with extreme learning machine based bias detection and correction technique to achieve a fully automatic segmentation of hippocampal subfields.Symmetric diffeomorphic registration driven by symmetric mutual information energy was implemented in atlas registration,which allows multi-modal image registration and accelerates execution time.An exponential function based label fusion strategy was proposed for the normalized similarity measure case in segmentation combination,which yields better combination accuracy.The test results show that this method is effective,especially for the larger subfields with an overlap of more than 80%,which is competitive with the current methods and is of potential clinical significance.

The HI gas and star formation in star-forming galaxies selected from ALFALFA

This paper presents the results of Hαimaging of 169 galaxies randomly selected from the α.40-SDSS catalog.The sample has excluded all low surface brightness galaxies (LSBGs) whose central surface brightness in B band (μ0(B)) fainter than 22.5 mag arcsec-2.It can be used as the counterparts sample to LSBGs.We observed their Hα and R band images by using the 2.16 m telescope at the Xinglong Observatory of the National Astronomical Observatories,Chinese Academy of Sciences (NAOC).The main goal of this work is to present the properties of those galaxies,together with Hαflux and star formation-,gas-,stellar mass-surface density.In addition,we confirm the correlations among HI content,stellar mass and star formation in ALFALFA galaxies.The HI mass increases with stellar mass,and the slope slows down at the higher stellar mass.The overall trend was that the specific star formation rate (s SFR) decreases with stellar mass,and the sSFR dropped sharply when the stellar mass is close to 1010.3~1010.5M⊙.The weak correlation between SFR/MHIand MHIimplies the HI contribute little to star formation.Our sample,which are mostly star-forming galaxies,follows the revisited Kennicutt-Schmidt law as well as the Kennicutt-Schmidt law.

Nuclear magnetic resonance study of the formation and dissociation process of nature gas hydrate in sandstone

In this work,the authors monitored the formation and dissociation process of methane hydrate in four different rock core samples through nuclear magnetic resonance(NMR)relaxation time(T_(2))and 2D imaging measurement.The result shows that the intensity of T_(2) spectra and magnetic resonance imaging(MRI)signals gradually decreases in the hydrate formation process,and at the same time,the T_(2) spectra move toward the left domain as the growth of hydrate in the pores of the sample accelerates the decay rate.The hydrate grows and dissociates preferentially in the purer sandstone samples with larger pore size and higher porosity.Significantly,for the sample with lower porosity and higher argillaceous content,the intensity of the T_(2) spectra also shows a trend of a great decrease in the hydrate formation process,which means that high-saturation gas hydrate can also be formed in the sample with higher argillaceous content.The changes in MRI of the sample in the process show that the formation and dissociation of methane hydrate can reshape the distribution of water in the pores.