Automatic measurement of three-phase contact angles in pore throats based on digital images

With the help of digital image processing technology, an automatic measurement method for the three-phase contact angles in the pore throats of the microfluidic model was established using the microfluidic water flooding experiment videos as the data source. The results of the new method were verified through comparing with the manual measurement data.On this basis, the dynamic changes of the three-phase contact angles under flow conditions were clarified by the contact angles probability density curve and mean value change curve. The results show that, for water-wetting rocks, the mean value of the contact angles is acute angle during the early stage of the water flooding process, and it increases with the displacement time and becomes obtuse angle in the middle-late stage of displacement as the dominant force of oil phase gradually changes from viscous force to capillary force. The droplet flow in the remaining oil occurs in the central part of the pore throats, without three-phase contact angle. The contact angles for the porous flow and the columnar flow change slightly during the displacement and present as obtuse angles in view of mean values, which makes the remaining oil poorly movable and thus hard to be recovered. The mean value of the contact angle for the cluster flow tends to increase in the flooding process, which makes the remaining oil more difficult to be recovered. The contact angles for the membrane flow are mainly obtuse angles and reach the highest mean value in the late stage of displacement, which makes the remaining oil most difficult to be recovered. After displacement, the remaining oils under different flow regimes are just subjected to capillary force, with obtuse contact angles, and the wettability of the pore throat walls in the microfluidic model tends to be oil-wet under the action of crude oil.

Estimating light interception using the color attributes of digital images of cotton canopies

Crop growth and yield depend on canopy light interception （LI）. To identify a low-cost and relatively efficient index for measuring LI, several color attributes of red-green-blue （RGB）, hue-saturation-intensity （HSI）, hue-saturation-value （HSV） color models and the component values of color attributes in the RGB color model were investigated using digital images at six cotton plant population densities in 2012-2014. The results showed that the LI values followed downward quadratic curves after planting. The red （R）, green （G） and blue （B） values varied greatly over the years, in accordance with Cai＇s research demonstrating that the RGB model is affected by outside light. Quadratic curves were fit to these color attributes at six plant population densities. Additionally, linear regressions of LI on every color attribute revealed that the hue （H） values in HSI and HSV were significantly linearly correlated with LI with a determination coefficient （R2）〉0.89 and a root mean square error （RMSE）=0.05. Thus, the H values in the HSI and HSV models could be used to measure LI, and this hypothesis was validated. The H values are new indexes for quantitatively estimating the LI of heterogeneous crop cano- pies, which will provide a theoretical basis for optimizing the crop canopy structure. However, further research should be conducted in other crops and under other growing and environmental conditions to verify this finding.

Soil Salinity and Soil Water Content Estimation Using Digital Images in Coastal Field:A Case Study in Yancheng City of Jiangsu Province,China

Soil is the essential part for agricultural and environmental sciences,and soil salinity and soil water content are both the important influence factors for sustainable development of agriculture and ecological environment.Digital camera,as one of the most popular and convenient proximal sensing instruments,has its irreplaceable position for soil properties assessment.In this study,we collected 52 soil samples and photographs at the same time along the coast in Yancheng City of Jiangsu Province.We carefully analyzed the relationship between soil properties and image brightness,and found that soil salt content had higher correlation with average image brightness value than soil water content.From the brightness levels,the high correlation coefficients between soil salt content and brightness levels concentrated on the high brightness values,and the high correlation coefficients between soil water content and brightness levels focused on the low brightness values.Different significance levels(P)determined different brightness levels related to soil properties,hence P value setting can be an optional way to select brightness levels as the input variables for modeling soil properties.Given these information,random forest algorithm was applied to develop soil salt content and soil water content inversion models using randomly 70%of the dataset,and the rest data for testing models.The results showed that soil salt content model had high accuracy(R_(v)^(2)=0.79,RMSE_(v)=12 g/kg,and RPD_(v)=2.18),and soil water content inversion model was barely satisfied(R_(v)^(2)=0.47,RMSE_(v)=3.04%,and RPD_(v)=1.38).This study proposes a method of modeling soil properties with a digital camera.Combining unmanned aerial vehicle(UAV),it has potential popularization and application value for precise agriculture and land management.

Applying Digital Image Processing to Evaluate a Extraction Method of Cartographic Features in Digital Images

A topic studied in cartography is to make the extraction of cartographic features that provide the update of cartographic maps more easily. For this reason many automatic routines were created with the intent to perform the features extraction. Despite of all studies about this, some features cannot be found by the algorithm or it can extract some pixels unduly. So the current article aims to show the results with the software development that uses the original and reference image to calculate some statistics about the extraction process. Furthermore, the calculated statistics can be used to evaluate the extraction process.

Simulation of Fracture Process of Lightweight Aggregate Concrete Based on Digital Image Processing Technology

The mechanical properties and failure mechanism of lightweight aggregate concrete(LWAC)is a hot topic in the engineering field,and the relationship between its microstructure and macroscopic mechanical properties is also a frontier research topic in the academic field.In this study,the image processing technology is used to establish a micro-structure model of lightweight aggregate concrete.Through the information extraction and processing of the section image of actual light aggregate concrete specimens,the mesostructural model of light aggregate concrete with real aggregate characteristics is established.The numerical simulation of uniaxial tensile test,uniaxial compression test and three-point bending test of lightweight aggregate concrete are carried out using a new finite element method-the base force element method respectively.Firstly,the image processing technology is used to produce beam specimens,uniaxial compression specimens and uniaxial tensile specimens of light aggregate concrete,which can better simulate the aggregate shape and random distribution of real light aggregate concrete.Secondly,the three-point bending test is numerically simulated.Thirdly,the uniaxial compression specimen generated by image processing technology is numerically simulated.Fourth,the uniaxial tensile specimen generated by image processing technology is numerically simulated.The mechanical behavior and damage mode of the specimen during loading were analyzed.The results of numerical simulation are compared and analyzed with those of relevant experiments.The feasibility and correctness of the micromodel established in this study for analyzing the micromechanics of lightweight aggregate concrete materials are verified.Image processing technology has a broad application prospect in the field of concrete mesoscopic damage analysis.

Method for evaluation of geological strength index of carbonate cliff rocks:Coupled hyperspectral-digital borehole image technique

The deterioration of unstable rock mass raised interest in evaluating rock mass quality.However,the traditional evaluation method for the geological strength index(GSI)primarily emphasizes the rock structure and characteristics of discontinuities.It ignores the influence of mineral composition and shows a deficiency in assessing the integrity coefficient.In this context,hyperspectral imaging and digital panoramic borehole camera technologies are applied to analyze the mineral content and integrity of rock mass.Based on the carbonate mineral content and fissure area ratio,the strength reduction factor and integrity coefficient are calculated to improve the GSI evaluation method.According to the results of mineral classification and fissure identification,the strength reduction factor and integrity coefficient increase with the depth of rock mass.The rock mass GSI calculated by the improved method is mainly concentrated between 40 and 60,which is close to the calculation results of the traditional method.The GSI error rates obtained by the two methods are mostly less than 10%,indicating the rationality of the hyperspectral-digital borehole image coupled evaluation method.Moreover,the sensitivity of the fissure area ratio(Sr)to GSI is greater than that of the strength reduction factor(a),which means the proposed GSI is suitable for rocks with significant fissure development.The improved method reduces the influence of subjective factors and provides a reliable index for the deterioration evaluation of rock mass.

Assessment and Visualization of Ki67 Heterogeneity in Breast Cancers through Digital Image Analysis

The Ki67 index (KI) is a standard clinical marker for tumor proliferation;however, its application is hindered by intratumoral heterogeneity. In this study, we used digital image analysis to comprehensively analyze Ki67 heterogeneity and distribution patterns in breast carcinoma. Using Smart Pathology software, we digitized and analyzed 42 excised breast carcinoma Ki67 slides. Boxplots, histograms, and heat maps were generated to illustrate the KI distribution. We found that 30% of cases (13/42) exhibited discrepancies between global and hotspot KI when using a 14% KI threshold for classification. Patients with higher global or hotspot KI values displayed greater heterogenicity. Ki67 distribution patterns were categorized as randomly distributed (52%, 22/42), peripheral (43%, 18/42), and centered (5%, 2/42). Our sampling simulator indicated analyzing more than 10 high-power fields was typically required to accurately estimate global KI, with sampling size being correlated with heterogeneity. In conclusion, using digital image analysis in whole-slide images allows for comprehensive Ki67 profile assessment, shedding light on heterogeneity and distribution patterns. This spatial information can facilitate KI surveys of breast cancer and other malignancies.

Anisotropy of Trabecular Bone from Ultra-Distal Radius Digital X-Ray Imaging: Effects on Bone Mineral Density and Age

Background: When applied to trabecular bone X-ray images, the anisotropic properties of trabeculae located at ultra-distal radius were investigated by using the trabecular bone scores (TBS) calculated along directions parallel and perpendicular to the forearm. Methodology: Data from more than two hundred subjects were studied retrospectively. A DXA (GE Lunar Prodigy) scan of the forearm was performed on each subject to measure the bone mineral density (BMD) value at the location of ultra-distal radius, and an X-ray digital image of the same forearm was taken on the same day. The values of trabecular bone score along the direction perpendicular to the forearm, TBSx, and along the direction parallel to the forearm, TBSy, were calculated respectively. The statistics of TBSx and TBSy were calculated, and the anisotropy of the trabecular bone, which was defined as the ratio of TBSy to TBSx and changed with subjects’ BMD and age, was reported and analyzed. Results: The results show that the correlation coefficient between TBSx and TBSy was 0.72 (p BMD and age was reported. The results showed that decreased trabecular bone anisotropy was associated with deceased BMD and increased age in the subject group. Conclusions: This study shows that decreased trabecular bone anisotropy was associated with decreased BMD and increased age.

The Application of Digital Optical 3D Image Analyzer Evaskin in The Evaluation of Wrinkles

To verify the effectiveness of digital optical 3D image analyzer EvaSKIN in the objective and quantitative evaluation of wrinkles.A total of 115 subjects were recruited,the facial images of the subjects were collected by digital optical 3D image analyzer and manual camera,the changes of crow’s feet with age were analyzed.Pictures obtained by manual photography can be directly used for observation and preliminary grading of wrinkles.However,the requirements for evaluators are high,and the results are prone to errors,which will affect the accuracy of the evaluation.Therefore,skilled raters are needed.Compared with the manual photography method,the digital optical 3D image analyzer EvaSKIN can realize three-dimensional extraction of wrinkles,and obtain the change trend of crow’s feet with age.20~30 years old,wrinkles begin to appear slowly;wrinkles will increase rapidly at the age of 30~50;The length of 50~60 year old wrinkles is basically fixed,the wrinkles develop longitudewise,gradually widen and deepen,and the area,depth and volume increase is obvious,and the skin aging condition is intensified.the digital optical 3D image analyzer EvaSKIN realizes the 3D extraction of wrinkles,quantifies the circumference,area,average depth,maximum depth and volume of wrinkles,realizes the objective and quantitative evaluation of wrinkle state,is more accurate in the measurement of wrinkles,and provides a new instrument and method for the evaluation of wrinkles.it is a perfect and supplement to the traditional evaluation methods,and to a certain extent,it helps the research and development and evaluation institutions of cosmetics to obtain more abundant and three-dimensional data support.

Correlations between mineral composition and mechanical properties of granite using digital image processing and discrete element method

This study investigated the correlations between mechanical properties and mineralogy of granite using the digital image processing(DIP) and discrete element method(DEM). The results showed that the X-ray diffraction(XRD)-based DIP method effectively analyzed the mineral composition contents and spatial distributions of granite. During the particle flow code(PFC2D) model calibration phase, the numerical simulation exhibited that the uniaxial compressive strength(UCS) value, elastic modulus(E), and failure pattern of the granite specimen in the UCS test were comparable to the experiment. By establishing 351 sets of numerical models and exploring the impacts of mineral composition on the mechanical properties of granite, it indicated that there was no negative correlation between quartz and feldspar for UCS, tensile strength(σ_(t)), and E. In contrast, mica had a significant negative correlation for UCS, σ_(t), and E. The presence of quartz increased the brittleness of granite, whereas the presence of mica and feldspar increased its ductility in UCS and direct tensile strength(DTS) tests. Varying contents of major mineral compositions in granite showed minor influence on the number of cracks in both UCS and DTS tests.

Microscopic damage evolution of anisotropic rocks under indirect tensile conditions: Insights from acoustic emission and digital image correlation techniques

The anisotropy induced by rock bedding structures is usually manifested in the mechanical behaviors and failure modes of rocks.Brazilian tests are conducted for seven groups of shale specimens featuring different bedding angles. Acoustic emission (AE) and digital image correlation (DIC) technologies are used to monitor the in-situ failure of the specimens. Furthermore, the crack morphology of damaged samples is observed through scanning electron microscopy (SEM). Results reveal the structural dependence on the tensile mechanical behavior of shales. The shale disk exhibits compression in the early stage of the experiment with varying locations and durations. The location of the compression area moves downward and gradually disappears when the bedding angle increases. The macroscopic failure is well characterized by AE event location results, and the dominant frequency distribution is related to the bedding angle. The b-value is found to be stress-dependent.The crack turning angle between layers and the number of cracks crossing the bedding both increase with the bedding angle, indicating competition between crack propagations. SEM results revealed that the failure modes of the samples can be classified into three types:tensile failure along beddings with shear failure of the matrix, ladder shear failure along beddings with tensile failure of the matrix, and shear failure along multiple beddings with tensile failure of the matrix.

Analysis of morphological characteristics of gravels based on digital image processing technology and self-organizing map

A comprehensive understanding of spatial distribution and clustering patterns of gravels is of great significance for ecological restoration and monitoring.However,traditional methods for studying gravels are low-efficiency and have many errors.This study researched the spatial distribution and cluster characteristics of gravels based on digital image processing technology combined with a self-organizing map(SOM)and multivariate statistical methods in the grassland of northern Tibetan Plateau.Moreover,the correlation of morphological parameters of gravels between different cluster groups and the environmental factors affecting gravel distribution were analyzed.The results showed that the morphological characteristics of gravels in northern region(cluster C)and southern region(cluster B)of the Tibetan Plateau were similar,with a low gravel coverage,small gravel diameter,and elongated shape.These regions were mainly distributed in high mountainous areas with large topographic relief.The central region(cluster A)has high coverage of gravels with a larger diameter,mainly distributed in high-altitude plains with smaller undulation.Principal component analysis(PCA)results showed that the gravel distribution of cluster A may be mainly affected by vegetation,while those in clusters B and C could be mainly affected by topography,climate,and soil.The study confirmed that the combination of digital image processing technology and SOM could effectively analyzed the spatial distribution characteristics of gravels,providing a new mode for gravel research.

Anisotropic creep behavior of soft-hard interbedded rock masses based on 3D printing and digital imaging correlation technology

Three-dimensional(3D)printing technology is increasingly used in experimental research of geotechnical engineering.Compared to other materials,3D layer-by-layer printing specimens are extremely similar to the inherent properties of natural layered rock masses.In this paper,soft-hard interbedded rock masses with different dip angles were prepared based on 3D printing(3DP)sand core technology.Uniaxial compression creep tests were conducted to investigate its anisotropic creep behavior based on digital imaging correlation(DIC)technology.The results show that the anisotropic creep behavior of the 3DP soft-hard interbedded rock mass is mainly affected by the dip angles of the weak interlayer when the stress is at low levels.As the stress level increases,the effect of creep stress on its creep anisotropy increases significantly,and the dip angle is no longer the main factor.The minimum value of the long-term strength and creep failure strength always appears in the weak interlayer within 30°–60°,which explains why the failure of the layered rock mass is controlled by the weak interlayer and generally emerges at 45°.The tests results are verified by comparing with theoretical and other published studies.The feasibility of the 3DP soft-hard interbedded rock mass provides broad prospects and application values for 3DP technology in future experimental research.

Assessing compressive strengths of mortar and concrete from digital images by machine learning techniques

Compressive strength is the most important metric of concrete quality.Various nondestructive and semi-destructive tests can be used to evaluate the compressive strength of concrete.In the present study,a new image-based machine learning method is used to predict concrete compressive strength,including evaluation of six different models.These include support-vector machine model and various deep convolutional neural network models,namely AlexNet,GoogleNet,VGG19,ResNet,and Inception-ResNet-V2.In the present investigation,cement mortar samples were prepared using each of the cement:sand ratios of 1:3,1:4,and 1:5,and using the water:cement ratios of 0.35 and 0.55.Cement concrete was prepared using the cement:sand:coarse aggregate ratios of 1:5:10,1:3:6,1:2:4,1:1.5:3 and 1:1:2,using the water:cement ratio of 0.5 for all samples.The samples were cut,and several images of the cut surfaces were captured at various zoom levels using a digital microscope.All samples were then tested destructively for compressive strength.The images and corresponding compressive strength were then used to train machine learning models to allow them to predict compressive strength based upon the image data.The Inception-ResNet-V2 models exhibited the best predictions of compressive strength among the models tested.Overall,the present findings validated the use of machine learning models as an efficient means of estimating cement mortar and concrete compressive strengths based on digital microscopic images,as an alternative nondestructive/semi-destructive test method that could be applied at relatively less expense.

Digital Image Encryption Algorithm Based on Double Chaotic Map and LSTM

In the era of network communication,digital image encryption(DIE)technology is critical to ensure the security of image data.However,there has been limited research on combining deep learning neural networks with chaotic mapping for the encryption of digital images.So,this paper addresses this gap by studying the generation of pseudo-random sequences(PRS)chaotic signals using dual logistic chaotic maps.These signals are then predicted using long and short-term memory(LSTM)networks,resulting in the reconstruction of a new chaotic signal.During the research process,it was discovered that there are numerous training parameters associated with the LSTM network,which can hinder training efficiency.To overcome this challenge and improve training efficiency,the paper proposes an improved particle swarm optimization(IPSO)algorithm to optimize the LSTM network.Subsequently,the obtained chaotic signal from the optimized model training is further scrambled,obfuscated,and diffused to achieve the final encrypted image.This research presents a digital image encryption(DIE)algorithm based on a double chaotic map(DCM)and LSTM.The algorithm demonstrates a high average NPCR(Number of Pixel Change Rate)of 99.56%and a UACI(Unified Average Changing Intensity)value of 33.46%,indicating a strong ability to resist differential attacks.Overall,the proposed algorithm realizes secure and sensitive digital image encryption,ensuring the protection of personal information in the Internet environment.

An efficient 3D cell-based discrete fracture-matrix flow model for digitally captured fracture networks

Complex hydraulic fracture networks are critical for enhancing permeability in unconventional reservoirs and mining indus-tries.However,accurately simulating the fluid flow in realistic fracture networks(compared to the statistical fracture net-works)is still challenging due to the fracture complexity and computational burden.This work proposes a simple yet efficient numerical framework for the flow simulation in fractured porous media obtained by 3D high-resolution images,aiming at both computational accuracy and efficiency.The fractured rock with complex fracture geometries is numerically constructed with a cell-based discrete fracture-matrix model(DFM)having implicit fracture apertures.The flow in the complex fractured porous media(including matrix flow,fracture flow,as well as exchange flow)is simulated with a pipe-based cell-centered finite volume method.The performance of this model is validated against analytical/numerical solutions.Then a lab-scale true triaxial hydraulically fractured shale sample is reconstructed,and the fluid flow in this realistic fracture network is simu-lated.Results suggest that the proposed method achieves a good balance between computational efficiency and accuracy.The complex fracture networks control the fluid flow process,and the opened natural fractures behave as primary fuid pathways.Heterogeneous and anisotropic features of fluid flow are well captured with the present model.

A Multi-Stage Security Solution for Medical Color Images in Healthcare Applications

This paper presents a robust multi-stage security solution based on fusion,encryption,and watermarking processes to transmit color healthcare images,efficiently.The presented solution depends on the features of discrete cosine transform(DCT),lifting wavelet transform(LWT),and singular value decomposition(SVD).The primary objective of this proposed solution is to ensure robustness for the color medical watermarked images against transmission attacks.During watermark embedding,the host color medical image is transformed into four sub-bands by employing three stages of LWT.The resulting low-frequency sub-band is then transformed by employing three stages of DCT followed by SVD operation.Furthermore,a fusion process is used for combining different watermarks into a single watermark image.This single fused image is then ciphered using Deoxyribose Nucleic Acid(DNA)encryption to strengthen the security.Then,the DNA-ciphered fused watermark is embedded in the host medical image by applying the suggested watermarking technique to obtain the watermarked image.The main contribution of this work is embedding multiple watermarks to prevent identity theft.In the presence of different multimedia attacks,several simulation tests on different colormedical images have been performed.The results prove that the proposed security solution achieves a decent imperceptibility quality with high Peak Signal-to-Noise Ratio(PSNR)values and high correlation between the extracted and original watermark images.Moreover,the watermark image extraction process succeeds in achieving high efficiency in the presence of attacks compared with related works.

Tensile strength and failure behavior of rock-mortar interfaces: Direct and indirect measurements

The tensile strength at the rock-concrete interface is one of the crucial factors controlling the failure mechanisms of structures,such as concrete gravity dams.Despite the critical importance of the failure mechanism and tensile strength of rock-concrete interfaces,understanding of these factors remains very limited.This study investigated the tensile strength and fracturing processes at rock-mortar interfaces subjected to direct and indirect tensile loadings.Digital image correlation(DIC)and acoustic emission(AE)techniques were used to monitor the failure mechanisms of specimens subjected to direct tension and indirect loading(Brazilian tests).The results indicated that the direct tensile strength of the rock-mortar specimens was lower than their indirect tensile strength,with a direct/indirect tensile strength ratio of 65%.DIC strain field data and moment tensor inversions(MTI)of AE events indicated that a significant number of shear microcracks occurred in the specimens subjected to the Brazilian test.The presence of these shear microcracks,which require more energy to break,resulted in a higher tensile strength during the Brazilian tests.In contrast,microcracks were predominantly tensile in specimens subjected to direct tension,leading to a lower tensile strength.Spatiotemporal monitoring of the cracking processes in the rock-mortar interfaces revealed that they show AE precursors before failure under the Brazilian test,whereas they show a minimal number of AE events before failure under direct tension.Due to different microcracking mechanisms,specimens tested under Brazilian tests showed lower roughness with flatter fracture surfaces than those tested under direct tension with jagged and rough fracture surfaces.The results of this study shed light on better understanding the micromechanics of damage in the rock-concrete interfaces for a safer design of engineering structures.

Increased retinal venule diameter as a prognostic indicator for recurrent cerebrovascular events:a prospective observational study

Microvasculature of the retina is considered an alternative marker of cerebral vascular risk in healthy populations.However,the ability of retinal vasculature changes,specifically focusing on retinal vessel diameter,to predict the recurrence of cerebrovascular events in patients with ischemic stroke has not been determined comprehensively.While previous studies have shown a link between retinal vessel diameter and recurrent cerebrovascular events,they have not incorporated this information into a predictive model.Therefore,this study aimed to investigate the relationship between retinal vessel diameter and subsequent cerebrovascular events in patients with acute ischemic stroke.Additionally,we sought to establish a predictive model by combining retinal veessel diameter with traditional risk factors.We performed a prospective observational study of 141 patients with acute ischemic stroke who were admitted to the First Affiliated Hospital of Jinan University.All of these patients underwent digital retinal imaging within 72 hours of admission and were followed up for 3 years.We found that,after adjusting for related risk factors,patients with acute ischemic stroke with mean arteriolar diameter within 0.5-1.0 disc diameters of the disc margin(MAD_(0.5-1.0DD))of≥74.14μm and mean venular diameter within 0.5-1.0 disc diameters of the disc margin(MVD_(0.5-1.0DD))of≥83.91μm tended to experience recurrent cerebrovascular events.We established three multivariate Cox proportional hazard regression models:model 1 included traditional risk factors,model 2 added MAD_(0.5-1.0DD)to model 1,and model 3 added MVD0.5-1.0DD to model 1.Model 3 had the greatest potential to predict subsequent cerebrovascular events,followed by model 2,and finally model 1.These findings indicate that combining retinal venular or arteriolar diameter with traditional risk factors could improve the prediction of recurrent cerebrovascular events in patients with acute ischemic stroke,and that retinal imaging could be a useful and non-invasive method for identifying high-risk patients who require closer monitoring and more aggressive management.

Fish maneuver analysis system based on sequence images

The aim is to establish an automatic system to analyze the maneuver performance of fish. A high speed camera （1 000 frame/s） is employed to record fast-start maneuver. Three steps are taken to analyze the kinematics： first, the midline in the first image is partitioned into equal interval lengths and the coordinates of all inter segmental points are saved. Secondly, these points coordinates are searched in the next frame with the digital image correlation （DIC） method, then these points are fitted with a spline curve function. Repeat this step until all the midlines are figured out frame by frame. Finally, according to the variety of midlines, the kinematics of the fast-start is calculated. Using this system to test carp C-start, the duration is divided into two stages： stage 1 is defined as the formation of the C shape and stage 2 as the return flip of the tail followed with forward motion. By tracing the middle line, the kinematic parameters of turning rate, centre of mass （CM） turning rate, CM turning radius, etc. are obtained.