Existing edge detection algorithms suffer from inefficient edge localization, noise sensitivity, and/or relatively poor automatic detection capability. Contemporary edge detection algorithms can be improved by targeting these problems to help bolster their performance. Grey system theory can be used to resolve the small data and poor information issues in the local information of uncertain systems. An automatic edge detection algorithm was developed in this study based on a grey prediction model to remedy these problems. Noise characteristics in grey images are used to deploy a noise-filtering algorithm based on local features. A mask with twenty-four edge direction information points (345°) was established based on edge line texture features. By compressing the amplitude of the sequence, the randomly oscillated grey prediction sequence can be converted into a smooth, new sequence. The discrete grey model (1,1) (DGM(1,1)) was established based on this new grey prediction sequence to obtain the grey prediction maximum value. A grey prediction image with enhanced edges was obtained by replacing the pixel value in the original image with the maximum grey prediction value. A grey prediction subtraction image with edges separated from non-edge points was also obtained by subtracting the original image from the grey prediction image. The optimal separation threshold in the grey prediction subtraction image can be determined via the global adaptive threshold selection method. The neighborhood search method was then deployed to remove stray points and burrs from the image after the target was separated from the background, creating the final edge image. Experiments were performed on a computer-simulated phantom to find that both the subjective visual effects and objective evaluation criteria are better under the proposed method than several other competitive methods. The proposed edge detection algorithm shows excellent edge detection ability and is highly robust to noise, though the grey prediction model needs further improvement to optimize the run time.

The traditional edge detection method is altogether inaccurate, nonadaptive, and particularly ineffective on noisy images. This paper proposes a novel edge detection algorithm based on gray entropy theory and local texture features. In the 3×3 neighborhood window, 28 comparison sequences are constructed according to local texture features. The reference sequence is composed of the median of all elements in the 3×3 neighborhood window. A total of 28 gray relation degrees as obtained by gray relation analysis between the 28 comparison sequences and reference sequences, as well as 28 gray relation degrees, are analyzed by gray entropy theory to initially filter the image. Gray entropy analysis is then performed on the comparison sequences composed of 28 texture features and reference sequences composed of the central pixel points of the filtered image to determine the maximum gray entropy difference. A comparative threshold adaptive acquisition method is designed to separate gray entropy difference sequence elements and identify all edge points accordingly. The simulation results show that the proposed algorithm effectively achieves adaptive edge detection and has strong anti-noise capability. The results of this study may provide a workable reference for edge information detection in the field of artificial intelligence (e.g., image recognition, pattern recognition applications).INDEX TERMS Image processing, image edge detection, gray relation analysis, gray entropy theory, textural feature analysis.

Aiming at the high requirement for pulse-repetition frequency of the existing single-beam synchronous scanning circumferential detection, which is difficult to use practically. The method of single-beam expanding scanning laser circumferential detection is proposed. Based on the principle of single-beam expanding scanning laser circumferential detection, the mode of scanning has an inherent defect of periodic detection blind area in the detection field. The method of one-way spreading laser line beam into fan-shaped beam is proposed. The analytical expression of the lowest scanning frequency and the pulse frequency are derived. Echo characteristics of cylindrical target and the section attenuation coefficient are analyzed. Mathematic model of cylindrical target echo power of pulsed expanding laser beam is established. The mathematical model of section attenuation coefficient of cylindrical object is established, and the variation of the section attenuation coefficient when the center line and the edge of the beam have different positions relative to the cylindrical target is analyzed. The expression of the position having the smallest section attenuation coefficient and the expression of largest angle between the adjacent pulse laser beams are obtained, then the influence of system parameters on the section attenuation coefficient is also discussed. The emphasis is placed on the influence of pulse frequency, beam angle and incidence angle on the ability to detect different diameter targets. As the laser pulse frequency increases, the detectable target diameter is smaller and the detection ability is stronger. Increasing the beam angle and lowering the laser incident angle are beneficial to reducing the minimum laser pulse frequency required to discover the target. The methods of calculating maximum beam angle and minimum pulse frequency under typical conditions of the detection system are presented. When the incident angles are <inline-formula><tex-math id="M1">\begin{document}${\text{π}}/3$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20181860_M1.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20181860_M1.png"/></alternatives></inline-formula>, <inline-formula><tex-math id="M2">\begin{document}${\text{π}}/4$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20181860_M2.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20181860_M2.png"/></alternatives></inline-formula> and <inline-formula><tex-math id="M3">\begin{document}${\text{π}}/6$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20181860_M3.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="7-20181860_M3.png"/></alternatives></inline-formula>, the maximum beam angle and the lowest pulse frequency are calculated for a cylindrical target with a diameter of 0.18 m at a detection distance of 6 m, the minimum pulse frequency decreases effectively after beam expansion. The results show that the pulse repetition frequency will be effectively reduced by slightly expanding the beam. This study may provide theoretical basis for designing and optimizing the single-beam pulsed laser circumferential detection.

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