A robust multiplicative watermarking technique for digital images in curvelet domain using normal inverse Gaussian distribution

Shaik, Ayesha; Masilamani, V.

doi:10.1007/s11042-022-14137-8

Cited by 8 publications

(5 citation statements)

References 45 publications

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“…The crack images used in this paper were obtained from the CFD dataset and collected dataset [10] of some roads in Zhangdian District, Zibo City, Shandong P In order to improve the richness of the self-acquired datasets and targets, and to the detection capability of the model in a certain aspect, this paper captures the pavement environment appearing in asphalt pavement, including lane marking ows, glare, debris, lane lines, water on the road surface, etc. As shown in Figu model can avoid misjudging the pavement scratches, lane markings, etc., in th Images depicting cracks with tree branch shadows can significantly enhance the a of the model in detecting cracks on the road surface under shadow; furthermore exhibiting cracks with strong exposures taken on sunny days and images of cra weak exposures captured on cloudy days can greatly enhance the accuracy of th in identifying cracks on the road surface under various weather and lighting con Experiments have proved that this method can effectively improve the generalizat ity of the model, the accuracy of the model in identifying multiple cracks under weather conditions, and the accuracy of the model in identifying multiple cracks As the image acquisition process is easily affected by various factors such equipment, and acquisition methods, the resulting pavement crack image may Gaussian, uniform, and salt-and-pepper (impulse) noise [11]. Confronted wi cracks or complex pavement environments, the probability density functions of types of noise are shown in Figure 2.…”

Section: Crack Image Datasetmentioning

confidence: 99%

“…These noises will cause the feature and det mation of the crack to not be prominent enough, resulting in the information of t ground region being stronger than the information of the crack region, thus affec effectiveness of the crack extraction. In addition, due to the large asphalt aggrega asphalt pavement, if the grayscale value of the asphalt aggregate gaps is close to t As the image acquisition process is easily affected by various factors such as light, equipment, and acquisition methods, the resulting pavement crack image may contain Gaussian, uniform, and salt-and-pepper (impulse) noise [11]. Confronted with small cracks or complex pavement environments, the probability density functions of various types of noise are shown in Figure 2.…”

Section: Crack Image Datasetmentioning

confidence: 99%

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Crack Segmentation Extraction and Parameter Calculation of Asphalt Pavement Based on Image Processing

Li,

Yin,

Zhang

2023

Sensors

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Crack disease is one of the most serious and common diseases in road detection. Traditional manual methods for measuring crack detection can no longer meet the needs of road crack detection. In previous work, the authors proposed a crack detection method for asphalt pavements based on an improved YOLOv5s model, which is a better model for detecting various types of cracks in asphalt pavements. However, most of the current research on automatic pavement crack detection is still focused on crack identification and location stages, which contributes little to practical engineering applications. Based on the shortcomings of the above work, and in order to improve its contribution to practical engineering applications, this paper proposes a method for segmenting and analyzing asphalt pavement cracks and identifying parameters based on image processing. The first step is to extract the crack profile through image grayscale, histogram equalization, segmented linear transformation, median filtering, Sauvola binarization, and the connected domain threshold method. Then, the magnification between the pixel area and the actual area of the calibration object is calculated. The second step is to extract the skeleton from the crack profile images of asphalt pavement using the Zhang–Suen thinning algorithm, followed by removing the burrs of the crack skeleton image using the connected domain threshold method. The final step is to calculate physical parameters, such as the actual area, width, segments, and length of the crack with images obtained from the crack profile and skeleton. The results show that (1) the method of local thresholding and connected domain thresholding can completely filter noise regions under the premise of retaining detailed crack region information. (2) The Zhang–Suen iterative refinement algorithm is faster in extracting the crack skeleton of asphalt pavement, retaining the foreground features of the image better, while the connected-domain thresholding method is able to eliminate the missed isolated noise. (3) In comparison to the manual calibration method, the crack parameter calculation method proposed in this paper can better complete the calculation of crack length, width, and area within an allowable margin of error. On the basis of this research, a windowing system for asphalt pavement crack detection, WSPCD1.0, was developed. It integrates the research results from this paper, facilitating automated detection and parameter output for asphalt pavement cracks.

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Section: Crack Image Datasetmentioning

confidence: 99%

Section: Crack Image Datasetmentioning

confidence: 99%

Crack Segmentation Extraction and Parameter Calculation of Asphalt Pavement Based on Image Processing

Li,

Yin,

Zhang

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…The essence of star sub-pixel gray reconstruction is to reconstruct the gray distribution of the adjacent pixels of the star to correct the position of the energy center of the star. Due to the two-dimensional Gaussian distribution of simulated star energy, its grayscale can be represented as [14,15]…”

Section: Subpixel Star Display Principlementioning

confidence: 99%

Research on subpixel partition correction method for simulating star position in star simulation system

Wu,

Wang,

Jia

et al. 2023

J. Inst.

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The accuracy of star position simulation in star simulation systems is a key factor affecting the accuracy of ground calibration experiments for star sensors. In order to solve the problem that the current simulation star position accuracy is restricted by the size of its constituent elements, In this paper, the mathematical model for simulating the star position correction and the gray distribution of the constituent elements is derived, and the functional representation of the azimuth and longitude correction, elevation and latitude correction of the simulated star position is established. Exploring the distribution law of star position simulation error and establishing a corrected sub interval based on it, achieving sub pixel level star position simulation accuracy. The experimental results show that after using the method proposed in this article, the accuracy of star position simulation has been improved by 1.74 times.

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“…The position of each star point in the simulated star map is determined by its gray energy center. The gray energy distribution of the star point can be expressed as follows [13][14][15]: where A represents the gray energy coefficient, σ represents the gaussian radius, and (xi,yi) represents the energy center coordinates of the star point. Under real conditions, there is polarization effect in the system.…”

Section: Exit Pupil Collimation Optical Systemmentioning

confidence: 99%

Study on Optimization Method of Polarization Balance for Weak Starlight System

Wu,

Sun,

et al. 2023

Preprint

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The accuracy of star position simulation is the key factor affecting the accuracy of ground calibration test of spacecraft attitude measurement system. To solve the impact of nonimaging polarized stray light on the simulation accuracy of star position in the optical engine of the system, the generation mechanism of non-imaging polarized stray light has been investigated, and an optimization method for polarization balance of the optical engine is proposed. The mathematical model of the incident light aperture angle and the ideal polarization parameter of the optical engine thin film is established, and the optimization evaluation function of polarization balance of the optical engine is constructed. An optical engine polarization balance film with the corresponding full-band binomial attenuation is <0.001 and the phase delay is <1°. Experimental results show that the simulation accuracy of the weak starlight simulation system is improved by 1.64 times using polarization balanced optical engine.

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A robust multiplicative watermarking technique for digital images in curvelet domain using normal inverse Gaussian distribution

Cited by 8 publications

References 45 publications

Crack Segmentation Extraction and Parameter Calculation of Asphalt Pavement Based on Image Processing

Crack Segmentation Extraction and Parameter Calculation of Asphalt Pavement Based on Image Processing

Research on subpixel partition correction method for simulating star position in star simulation system

Study on Optimization Method of Polarization Balance for Weak Starlight System

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