An image matching method based on the analysis of grey correlation degree and feature points

Ding, Zishuo; Qian, Shuo; Li, Yulin; Li, Zhaohui

doi:10.1109/naecon.2014.7045795

Cited by 6 publications

(5 citation statements)

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“…At the same time, it requires less prior knowledge of the target and is easy to implement. However, it has high sensitivity to the gray distortion of the target, which makes the possibility of cumulative error larger [1]. The latter is less sensitive to the geometric and gray distortion of the target, which greatly improves the recognition accuracy [2].…”

Section: Introductionmentioning

confidence: 99%

Research on infrared image classification algorithm based on improved KNN

WANG,

2024

Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023)

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This paper focused on the improved KNN infrared image classification algorithm. In the process of image feature extraction, particle swarm optimization (PSO) was introduced to solve the problem that the iterative speed of objective function optimization was relatively slow in the traditional ICA algorithm. In this way, the global optimal solution could be found quickly when the objective function was optimized, which greatly reduced the computational complexity of ICA algorithm. In order to solve the ambiguity problem of KNN classification in image classification, error correcting coding theory was introduced, which was combined with KNN classification algorithm to classify multi class objects. Experiments showed that the improved algorithm in this paper had obvious optimization in classification, strong anti error classification ability and high accuracy.

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Section: Introductionmentioning

confidence: 99%

Research on infrared image classification algorithm based on improved KNN

WANG,

2024

Second International Conference on Electrical, Electronics, and Information Engineering (EEIE 2023)

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“…Shut-off valves play a significant role in the oil, chemical and gas processing industries [2]. Corrosion, continuous contact with the fluid being pumped, operation at elevated temperatures and pressures, and other unfavorable conditions can cause leakage of shut-off valves [2,3]. Improper operation of the valve can lead to losses, decreased energy efficiency, and compromised safety of technological processes.…”

Section: Introductionmentioning

confidence: 99%

“…The acoustic leak detection technique is widely employed as an express method for verifying the tightness of valve gates [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Detection of Gate Valve Leaks through the Analysis Fractal Characteristics of Acoustic Signal

Zagretdinov,

Ziganshin,

Izmailova

et al. 2024

Fractal Fract

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This paper considers the possibility of using monofractal and multifractal analysis of acoustic signals to detect water leaks through gate valves. Detrended fluctuation analysis (DFA) and multifractal detrended fluctuation analysis (MF-DFA) were used. Experimental studies were conducted on a ½-inch nominal diameter wedge valve, which was fitted to a ¾-inch nominal diameter steel pipeline. The water leak was simulated by opening the valve. The resulting leakage rates for different valve opening conditions were 5.3, 10.5, 14, 16.8, and 20 L per minute (L/min). The Hurst exponent for acoustic signals in a hermetically sealed valve is at the same level as a deterministic signal, while the width of the multifractal spectrum closely matches that of a monofractal process. When a leak occurs, turbulent flow pulsations appear, and with small leak sizes, the acoustic signals become anticorrelated with a high degree of multifractality. As the leakage increases, the Hurst exponent also increases and the width of the multifractal spectrum decreases. The main contributor to the multifractal structure of leak signals is small, noise-like fluctuations. The analysis of acoustic signals using the DFA and MF-DFA methods enables determining the extent of water leakage through a non-sealed gate valve. The results of the experimental studies are in agreement with the numerical simulations. Using the Ansys Fluent software (v. 19.2), the frequencies of flow vortices at different positions of gate valve were calculated. The k-ω SST turbulence model was employed for calculations. The calculations were conducted in a transient formulation of the problem. It was found that as the leakage decreases, the areas with a higher turbulence eddy frequency increase. An increase in the frequency of turbulent fluctuations leads to enhanced energy dissipation. Some of the energy from ordered processes is converted into the energy of disordered processes.

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“…Takasu et al offered an edge detection algorithm that can be applied to image matching [10]. Ding et al brought up an image matching method based on a gray relational degree and feature point analysis, which has high matching precision and robustness and can eliminate the impact of stretching, rotation, and illumination changes [11]. Konar aims at designing a fuzzy matching algorithm that would automatically recognize an unknown ballet posture [12].…”

Section: Introductionmentioning

confidence: 99%

Research on the algorithm of electromagnetic leakage reduction and sequence of image migration feature retrieval

Miao

2019

J Image Video Proc.

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When the computer is working, it will transmit the electromagnetic leakage signal containing the video information and receive and process the electromagnetic leakage signal within a certain distance, which can reproduce the screen information and form the electromagnetic leakage restoration sequence image. Due to the noise in the receiving process and the fluctuation of the video line and field signal, the image of the electromagnetic leakage restoration sequence will be blurred and will drift between frames. The multi-frame cumulative averaging method can theoretically improve the signal-to-noise ratio of the reconstructed image, but the offset of the reconstructed image sequence caused by the electromagnetic leakage will bring adverse effects. Firstly, this paper analyzes the noise of electromagnetic leakage emission and restoration sequence images and the method of multi-frame cumulative averaging, as well as the cumulative averaging effect of multi-frame sequence images under the influence of image offset. Secondly, on the basis of theoretical analysis, an algorithm of image migration feature retrieval for electromagnetic leakage restoration sequence is proposed and validated, which achieves more accurate inter-frame matching, automatic offset calculation, and multi-frame sequence image accumulation and enhances the recognition of the electromagnetic leakage restoration image. Lastly, different algorithms are compared, and their effects are evaluated as well.

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An image matching method based on the analysis of grey correlation degree and feature points

Cited by 6 publications

References 0 publications

Research on infrared image classification algorithm based on improved KNN

Research on infrared image classification algorithm based on improved KNN

Detection of Gate Valve Leaks through the Analysis Fractal Characteristics of Acoustic Signal

Research on the algorithm of electromagnetic leakage reduction and sequence of image migration feature retrieval

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