PSO (Particle Swarm Optimization) based infrared image segmentation method of Niblack power equipment

A particle swarm optimization, infrared image technology, applied in the field of image processing, can solve problems such as low contrast, target device and background distinction, and achieve the effect of reducing the impact of segmentation effect and improving integrity

Active Publication Date: 2017-08-29
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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Problems solved by technology

Most of the above algorithms are based on global thresholds, and it is difficult to distinguish the...

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  • PSO (Particle Swarm Optimization) based infrared image segmentation method of Niblack power equipment
  • PSO (Particle Swarm Optimization) based infrared image segmentation method of Niblack power equipment
  • PSO (Particle Swarm Optimization) based infrared image segmentation method of Niblack power equipment

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[0029] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is carried out on the premise of the technical solution of the present invention, and detailed implementation and specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0030] like figure 1 As shown, the present embodiment provides a Niblack power equipment infrared image segmentation method based on particle swarm optimization, comprising the following steps:

[0031] 1) Obtain an infrared image, divide the infrared image into q non-overlapping continuous rectangular neighborhoods, and calculate the gray-scale mean value and gray-scale standard variance of each of the rectangular neighborhoods.

[0032] In this embodiment, the imported resolution is 320×240 infrared original image g(x,y) of electric equipment, such as figure 2 As shown, when the ...

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Abstract

The invention relates to a PSO based infrared image segmentation method of Niblack power equipment. The method comprises the following steps that 1) an infrared image is obtained and divided into q non-overlapped continuous rectangular neighborhoods, and a grayscale mean value and a grayscale standard deviation of each rectangular neighborhood are calculated; 2) a threshold optimization searching interval corresponding to each rectangular neighborhood is obtained according to a set step length, a q-dimensional particle swarm solution space is formed, an inter-class deviation serves as a PSO fitness function, and the q-dimensional particle swarm solution space is searched automatically for an optimal segmentation threshold T*, which enables a maximal inter-class deviation, corresponding to each rectangular neighborhood; and 3) and each rectangular neighborhood is binarized according to the optimal segmentation threshold, obtained in the step 2), of the rectangular neighborhood. Compared with the prior art, the problem of infrared image over-segmentation caused by a traditional global threshold segmentation method is solved.

Description

technical field [0001] The invention relates to an image processing method, in particular to a method for segmenting infrared images of Niblack power equipment based on particle swarm optimization. Background technique [0002] In recent years, the substation online monitoring system has been widely used. Infrared cameras, visible light cameras and visible light and infrared images are sent back to the main control room for manual analysis. Although this method reduces the labor of manual data collection, it fails to Get rid of dependence on manual diagnosis. With the continuous development of artificial intelligence and image processing technology, intelligent diagnosis technology has begun to be applied to power equipment fault diagnosis. The intelligent diagnosis method is mainly divided into three steps. First, find out the equipment target area from the infrared image, that is, the region of interest (ROI), then extract relevant information from the area, and finally c...

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Application Information

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IPC IPC(8): G06T7/11G06T7/136
CPCG06T7/11G06T7/136G06T2207/10048
Inventor 崔昊杨李鑫霍思佳郭文诚李亚束江葛晨航刘晨斐马宏伟
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
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