Integrating image processing and deep learning for effective analysis and classification of dust pollution in mining processes

A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines.The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images.The research reveals both linear and logarithmic correlations between the gray features,fractal dimension,and dust mass,while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness.An integrated hazardous index is developed,including a logarithmic correlation between the index and dust mass,and a four-category dataset is subsequently prepared for the deep learning framework.Based on the range of the hazardous index,the dust images are divided into four categories.Subsequently,a dust risk classifcation system is established using the deep learning model,which exhibits a high degree of performance after the training process.Notably,the model achieves a testing accuracy of 95.3%,indicating its efectiveness in classifying diferent levels of dust pollution,and the precision,recall,and F1-score of the system confrm its reliability in analyzing dust pollution.Overall,the proposed method provides a reliable and efcient way to monitor and analyze dust pollution in mines.

A Multi-Stream Scrambling and DNA Encoding Method Based Image Encryption

Information security has emerged as a key problem in encryption because of the rapid evolution of the internet and networks.Thus,the progress of image encryption techniques is becoming an increasingly serious issue and considerable problem.Small space of the key,encryption-based low confidentiality,low key sensitivity,and easily exploitable existing image encryption techniques integrating chaotic system and DNA computing are purposing the main problems to propose a new encryption technique in this study.In our proposed scheme,a three-dimensional Chen’s map and a one-dimensional Logistic map are employed to construct a double-layer image encryption scheme.In the confusion stage,different scrambling operations related to the original plain image pixels are designed using Chen’s map.A stream pixel scrambling operation related to the plain image is constructed.Then,a block scrambling-based image encryption-related stream pixel scrambled image is designed.In the diffusion stage,two rounds of pixel diffusion are generated related to the confusing image for intra-image diffusion.Chen’s map,logistic map,and DNA computing are employed to construct diffusion operations.A reverse complementary rule is applied to obtain a new form of DNA.A Chen’s map is used to produce a pseudorandom DNA sequence,and then another DNA form is constructed from a reverse pseudorandom DNA sequence.Finally,the XOR operation is performed multiple times to obtain the encrypted image.According to the simulation of experiments and security analysis,this approach extends the key space,has great sensitivity,and is able to withstand various typical attacks.An adequate encryption effect is achieved by the proposed algorithm,which can simultaneously decrease the correlation between adjacent pixels by making it near zero,also the information entropy is increased.The number of pixels changing rate(NPCR)and the unified average change intensity(UACI)both are very near to optimal values.

Two-Stage Driving Circuit for One-Chip TFT-LCD Driver IC

A two-stage driving circuit of a one-chip TFT-LCD driver IC for portable electronic devices is proposed. The driving buffers of the new circuit are built in the γ-correction circuit rather than in the source driver. The power consumption,die area, and driving capability of the driving circuit are discussed in detail. For a two-stage driving circuit with 13 driving buffers, the settling time of the driving voltage within 0.2% error is about 19.2μs when 396 pixel-loads are driven by the same grayscale voltage. The quiescent current of the whole driving circuit is 518μ~A,and the power consumption can be reduced by 77%. The proposed driving circuit is successfully applied in a 132RGB × 176-dot,260k color one-chip driver IC developed by us for the TFT-LCD of mobile phone, and it can also be used in other portable electronic devices, such as PDAs and digital cameras.

COLOR AC-PDP ENHANCEMENT OF LOW LEVELS IMAGE QUALITY WITH DYNAMIC MODIFYING SUB-FIELDS CODE

Based on the "Grayscales average distribution" method which equally distributes the input gray levels to output gray levels, three improved methods named: "Reduce the gray range expressed by the less significant subfields", "Low levels preset" and "Modify the exponent of inverse-gamma function" are proposed in this paper. Using these methods, the inverse-gamma relation subfields code can be obtained easily which can improve the low level expressions of AC-PDP. And a program, "gray scales distribution validate program", which can enhance the expressions of the demanded gray levels range, is also proposed in this paper.

Fractal and microscopic quantitative characterization of unclassified tailings flocs

A series of laboratory investigations are conducted to analyze the effect of flocculant type on the spatial morphology and microstructural characteristics of flocs during the flocculation and settling of tailings.Four flocculant types(i.e.,ZYZ,JYC-2,ZYD,and JYC-1)are considered in this study.The fractal characteristics and internal structures of tailings flocs with different flocculant types and settlement heights are analyzed by conducting scanning electron microscopy and X-ray micro-computed tomography scanning experiments based on the fractal theory.Results show that unclassified tailings flocs are irregular clusters with fractal characteristics,and the flocculation effect of the four flocculant types has the following trend:ZYZ>JYC-2>ZYD>JYC-1.The size and average grayscale value of tailings flocs decrease with the increase in settlement height.The average grayscale values at the top and bottom are 144 and 103,respectively.The settlement height remarkably affects the pore distribution pattern,as reflected in the constructed three-dimensional pore model of tailings flocs.The top part of flocs has relatively good penetration,whereas the bottom part of flocs has mostly dispersed pores.The number of pores increases exponentially with the increase in settlement height.By contrast,the size of pores initially increases and subsequently decreases with the increase in settlement height.

Calibrating the linearity between grayscale and element content for X-ray KES imaging of alloys

Doped elements in alloys significantly impact their performance.Conventional methods usually sputter the surface material of the sample,or their performance is limited to the surface of alloys owing to their poor penetration ability.The X-ray K-edge subtraction(KES)method exhibits great potential for the nondestructive in situ detection of element contents in alloys.However,the signal of doped elements usually deteriorates because of the strong absorption of the principal component and scattering of crystal grains.This in turn prevents the extensive application of X-ray KES imaging to alloys.In this study,methods were developed to calibrate the linearity between the grayscale of the KES image and element content.The methods were aimed at the sensitive analysis of elements in alloys.Furthermore,experiments with phantoms and alloys demonstrated that,after elaborate calibration,X-ray KES imaging is capable of nondestructive and sensitive analysis of doped elements in alloys.

Cement Pavement Surface Crack Detection Based on Image Processing

This article introduces the application of image recognition technology in cement pavement crack detection and put forward to method fordetermining threshold about grayscale stretching. This algorithm is designed for binarization which has a self-adaptive characteristic. After theimage is preprocessed, we apply 2D wavelet and Laplace operator to process the image. According to the characteristic of pixel of gray image, analgorithm designed on binarization for Binary image. The feasibility of this method can be verified the image processed by comparing with theresults of three algorithms: Otsu method, iteration method and fixed threshold method.

Value of duplex doppler ultrasonography in non-invasive assessment of children with chronic liver disease

AIM:To investigate the value of duplex Doppler ultrasonography (US) in the assessment of the hemodynamics of the portal and hepatic veins in a cohort of children with chronic liver disease (CLD) and to detect any relationship between the US changes,etiology and severity (or stage) of CLD. METHODS:We prospectively enrolled 25 children with biopsy-proven CLD. Thirteen had cirrhosis (aged 8.9 ± 2.0 years) and 12 had chronic hepatitis (aged 9.3 ± 2.3 years). Gray scale and color-coded duplex Doppler US were performed for all,as well as 30 healthy age and sex-matched controls. Findings were correlated with clinical,laboratory and histopathological characteristics. RESULTS:Prominent caudate lobe was detected in 100% of cirrhotics,but none of the chronic hepatitis or controls. Thickened lesser omentum and loss of the triphasic waveform of the hepatic vein were present in 69.2% and 53.8% of cirrhotics vs 33.3% and 8.3% of chronic hepatitis respectively. Portal vein flow velocity was significantly lower (P < 0.0001) and the congestion index was significantly higher (P < 0.005) in both patient groups compared to controls. Child-Pugh's staging showed a positive correlation with both abnormal hepatic vein waveform and direction of portal blood flow; and a negative correlation with both hepatic and portal vein flow velocities. No correlation with the etiology of CLD could be detected. CONCLUSION:Duplex Doppler added to grayscale US can detect significant morphologic and portal hemodynamic changes that correlate with the severity (stage) of CLD,but not with etiology.

Iterative circle fitting based on circular attracting factor

An intuitive method for circle fitting is proposed. Assuming an approximate circle(CA,n) for the fitting of some scattered points, it can be imagined that every point would apply a force to CA,n, which all together form an overall effect that "draws" CA,n towards best fitting to the group of points. The basic element of the force is called circular attracting factor(CAF) which is defined as a real scalar in a radial direction of CA,n. An iterative algorithm based on this idea is proposed, and the convergence and accuracy are analyzed. The algorithm converges uniformly which is proved by the analysis of Lyapunov function, and the accuracy of the algorithm is in accord with that of geometric least squares of circle fitting. The algorithm is adopted to circle detection in grayscale images, in which the transferring to binary images is not required, and thus the algorithm is less sensitive to lightening and background noise. The main point for the adaption is the calculation of CAF which is extended in radial directions of CA,n for the whole image. All pixels would apply forces to CA,n, and the overall effect of forces would be equivalent to a force from the centroid of pixels to CA,n. The forces from would-be edge pixels would overweigh that from noisy pixels, so the following approximate circle would be of better fitting. To reduce the amount of calculation, pixels are only used in an annular area including the boundary of CA,n just in between for the calculation of CAF. Examples are given, showing the process of circle fitting of scattered points around a circle from an initial assuming circle, comparing the fitting results for scattered points from some related literature, applying the method proposed for circular edge detection in grayscale images with noise, and/or with only partial arc of a circle, and for circle detection in BGA inspection.

Blind Detection of LSB Steganography in Grayscale Images

There are many detectors for the least significant bit(LSB)steganography which is broadly used in hiding information in the digital images.The length of the hidden information is one of the most important parameters in detecting steganographic information.Using 2-D gradient of a pixel and the distance between variables the proposed method gives the length of hidden information in natural grayscale images without original image.Extensive experimental results show good performance even at low embedding rate compared with other methods.Furthermore,the proposed method also works well disregarding the status of the embedded information.

Grayscale Mapping of Historically Irrigated LandsUsing GIS

This document describes the use of grayscale mapping and GIS for identification of historical irrigated lands. Historical irrigated lands form the basis for water rights—a private property right in New Mexico that is bought and sold on the open market. Identification of irrigated land on historical photography is both a science and an art. Grayscale mapping of historic black and white photographs can aid in the identification of irrigated lands. GIS allows historical images to be geo-referenced and area computations to be performed on polygons that define the irrigated lands.

The Study of Otsu Algorithm Applied in the Measuring of Ash Proportion

To further improve the boiler ash ratio detection methods and resource utilization, through image processing technology for boiler ash ratio analysis, the article first studied the one-dimensional Otsu algorithm, and then for the one-dimensional Otsu algorithm, in order to improve the accuracy of the algorithm, then it puts forward a two-dimensional Otsu algorithm. Finally the two-dimensional Otsu algorithm combined with the one-dimensional Otsu algorithm and the improved Otsu algorithm. By analyzing the improved Otsu algorithm, this paper considers the pixel gray value, neighborhood information, excluding light, noise and the relative efficiency of one-dimensional Otsu algorithm higher accuracy. The relative dimensional Otsu algorithm operating efficiency has been greatly improved. Improved Otsu algorithm in dealing with boiler ash ratio detection has played a very good part in the ecological environment, economic development and some other important aspects.

Semi-automated detection of rangeland runoff and erosion control berms using high-resolution topography data

An inventory of topographic modifications is essential to addressing their impacts on hydrological and morphological processes in human-altered watersheds.However,such inventories are generally lacking.This study presents two workflows for semi-automatic detection of linear earthen runoff and erosion control berms in rangelands using high-resolution topographic data.The workflows consist of initial object identification by applying either morphological grayscale reconstruction(MGR)or the Geomorphon(GEO)method,followed by identification refinements through filters based on objects’horizontal and vertical information.Three sites were selected within the Altar Valley,Arizona,in the southwestern United States.One site was used for developing workflows and optimizing filter thresholds,and the other two sites were used to validate workflows.The results showed that:1)The MGR-based workflow methodology could produce final precision and detection rates of up to 92%and 75%,respectively,and take less than 5 s for a 10.1 km^(2) site;2)The workflow based on the MGR method yielded greater identification accuracy than did the GEO workflow;3)Object length,orientation,and eccentricity were important characteristics for identifying earthen berms,and are sensitive to general channel flow direction and berm shape;4)Manual interrogation of topographic data and imagery can significantly improve identification precision rates.The proposed workflows will be useful for developing inventories of runoff and erosion control structures in support of sustainable rangeland management.

Multiscale method for identifying and marking the multiform fractures from visible-light rock-mass images

Multiform fractures have a direct impact on the mechanical performance of rock masses.To accurately identify multiform fractures,the distribution patterns of grayscale and the differential features of fractures in their neighborhoods are summarized.Based on this,a multiscale processing algorithm is proposed.The multiscale process is as follows.On the neighborhood of pixels,a grayscale continuous function is constructed using bilinear interpolation,the smoothing of the grayscale function is realized by Gaussian local filtering,and the grayscale gradient and Hessian matrix are calculated with high accuracy.On small-scale blocks,the pixels are classified by adaptively setting the grayscale threshold to identify potential line segments and mini-fillings.On the global image,potential line segments and mini-fillings are spliced together by progressing the block frontier layer-by-layer to identify and mark multiform fractures.The accuracy of identifying multiform fractures is improved by constructing a grayscale continuous function and adaptively setting the grayscale thresholds on small-scale blocks.And the layer-by-layer splicing algorithm is performed only on the domain of the 2-layer small-scale blocks,reducing the complexity.By using rock mass images with different fracture types as examples,the identification results show that the proposed algorithm can accurately identify the multiform fractures,which lays the foundation for calculating the mechanical parameters of rock masses.

3D micro-devices for enhancing the lateral resolution in optical microscopy

Although optical microscopy is a widely used technique across various multidisciplinary fields for inspecting small-scale objects,surfaces or organisms,it faces a significant limitation:the lateral resolution of optical microscopes is fundamentally constrained by light diffraction.Dielectric micro-spheres,however,offer a promising solution to this issue as they are capable of significantly enhancing lateral resolution through extraordinary phenomena,such as a photonic nanojet.Building upon the potential of dielectric micro-spheres,this paper introduces a novel approach for fabricating 3D micro-devices designed to enhance lateral resolution in optical microscopy.The proposed 3D micro-device comprises a modified coverslip and a micro-sphere,facilitating easy handling and integration into any existing optical microscope.To manufacture the device,two advanced femtosecond laser techniques are employed:femtosecond laser ablation and multi-photon lithography.Femtosecond laser ablation was employed to create a micro-hole in the coverslip,which allows light to be focused through this aperture.Multi-photon lithography was used to fabricate a micro-sphere with a diameter of 20μm,along with a cantilever that positions the above the processed micro-hole and connect it with the coverslip.In this context,advanced processing strategies for multi-photon lithography to produce a micro-sphere with superior surface roughness and almost perfect geometry(λ/8)from a Zr-based hybrid photoresist are demonstrated.The performance of the micro-device was evaluated using Mirau-type coherence scanning interferometry in conjunction with white light illumination at a central wavelength of 600 nm and a calibration grid(Λ=0.28μm,h>50 nm).Here,the 3D micro-device proved to be capable of enhancing lateral resolution beyond the limits achievable with conventional lenses or microscope objectives when used in air.Simultaneously,it maintained the high axial resolution characteristic of Mirau-type coherence scanning interferometry.The results and optical properties of the micro-sphere were analyzed and further discussed through simulations.

Laser speckle grayscale lithography:a new tool for fabricating highly sensitive flexible capacitive pressure sensors

Achieving a high sensitivity for practical applications has always been one of the main developmental directions for wearable flexible pressure sensors.This paper introduces a laser speckle grayscale lithography system and a novel method for fabricating random conical array microstructures using grainy laser speckle patterns.Its feasibility is attributed to the autocorrelation function of the laser speckle intensity,which adheres to a first-order Bessel function of the first kind.Through objective speckle size and exposure dose manipulations,we developed a microstructured photoresist with various micromorphologies.These microstructures were used to form polydimethylsiloxane microstructured electrodes that were used in flexible capacitive pressure sensors.These-1 sensors exhibited an ultra-high sensitivity:19.76 kPa for the low-pressure range of 0-100 Pa.Their minimum detection threshold was 1.9 Pa,and they maintained stability and resilience over 10,000 test cycles.These sensors proved to be adept at capturing physiological signals and providing tactile feedback,thereby emphasizing their practical value.

Research on Defect Detection of Wind Turbine Blades Based on Morphology and Improved Otsu Algorithm Using Infrared Images

To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades(WTB),this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm.First,mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image.The algorithm employs entropy as the objective function to guide the iteration process of image enhancement,selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations,effectively enhancing the detail features of defect regions and improving the contrast between defects and background.Afterwards,grayscale inversion is performed on the enhanced infrared defect image to better adapt to the improved Otsu algorithm.Finally,by introducing a parameter K to adjust the calculation of inter-class variance in the Otsu method,the weight of the target pixels is increased.Combined with the adaptive iterative threshold algorithm,the threshold selection process is further fine-tuned.Experimental results show that compared to traditional Otsu algorithms and other improvements,the proposed method has significant advantages in terms of defect detection accuracy and reducing false positive rates.The average defect detection rate approaches 1,and the average Hausdorff distance decreases to 0.825,indicating strong robustness and accuracy of the method.

Centimeter scale color printing with grayscale lithography

Structural color from artificial structures,due to its environmental friendliness and excellent durability,represents a route for color printing applications.Among various physical mechanisms,the Fabry–Perot(F–P)cavity effect provides a powerful way to generate vivid colors in either the reflection or transmission direction.Most of the previous F–P type color printing works rely on electron beam grayscale lithography,however,with this technique it is challenging to make large-area and low-cost devices.To circumvent this constraint,we propose to fabricate the F–P type color printing device by the laser grayscale lithography process.The F–P cavity consists of two thin silver films as mirrors and a photoresist film with a spatially variant thickness as the spacer layer.By controlling the laser exposure dose pixel by pixel,a centimeter-scale fullcolor printing device with a spatial resolution up to 5μm×5μm is demonstrated.The proposed large area color printing device may have great potential in practical application areas such as color displays,hyperspectral imaging,advanced painting,and so on.

Fractional differential approach to detecting textural features of digital image and its fractional differential filter implementation

This paper mainly discusses fractional differential approach to detecting textural features of digital image and its fractional differential filter. Firstly, both the geo- metric meaning and the kinetic physical meaning of fractional differential are clearly explained in view of information theory and kinetics, respectively. Secondly, it puts forward and discusses the definitions and theories of fractional stationary point, fractional equilibrium coefficient, fractional stable coefficient, and fractional grayscale co-occurrence matrix. At the same time, it particularly discusses frac- tional grayscale co-occurrence matrix approach to detecting textural features of digital image. Thirdly, it discusses in detail the structures and parameters of nxn any order fractional differential mask on negative x-coordinate, positive x-coordi- nate, negative y-coordinate, positive y-coordinate, left downward diagonal, left upward diagonal, right downward diagonal, and right upward diagonal, respectively. Furthermore, it discusses the numerical implementation algorithms of fractional differential mask for digital image. Lastly, based on the above-mentioned discus- sion, it puts forward and discusses the theory and implementation of fractional differential filter for digital image. Experiments show that the fractional differential-based image operator has excellent feedback for enhancing the textural details of rich-grained digital images.

Dynamic infrared scene simulation using grayscale modulation of digital micro-mirror device

Dynamic infrared scene simulation is for discovering and solving the problems encountered in designing, developing and manufacturing infrared imaging guidance weapons. The infrared scene simulation is explored by using the digital grayscale modulation method. The infrared image modulation model of a digital micro-mirror device （DMD） is established and then the infrared scene simulator prototype which is based on DMD grayscale modulation is developed. To evaluate its main parameters such as resolution, contrast, minimum temperature difference, gray scale, various DMD subsystems such as signal decoding, image normalization, synchronization drive, pulse width modulation （PWM） and DMD chips are designed. The infrared scene simulator is tested on a certain infrared missile seeker. The test results show preliminarily that the infrared scene simulator has high gray scale, small geometrical distortion and highly resolvable imaging resolution and contrast and yields high-fidelity images, thus being able to meet the requirements for the infrared scene simulation inside a laboratory.