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Rotor winding image detection method fusing region distribution characteristics and edge scale angle information

A technology of regional distribution and image detection, which is applied in image analysis, image data processing, instruments, etc., can solve the problems of similarity value fluctuations, long calculation time of standard templates, etc., achieve high accuracy, improve detection accuracy, and work efficiency high effect

Active Publication Date: 2018-11-02
SOUTHEAST UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Aiming at the problem that the similarity value fluctuates when the image to be tested is matched with different template images, this paper proposes a rotor winding image detection method that combines regional distribution characteristics and edge scale angle information, which effectively avoids the randomness of the template selection. The impact of detection accuracy, but also avoid the problem of too many standard templates and long calculation time

Method used

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  • Rotor winding image detection method fusing region distribution characteristics and edge scale angle information
  • Rotor winding image detection method fusing region distribution characteristics and edge scale angle information
  • Rotor winding image detection method fusing region distribution characteristics and edge scale angle information

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Embodiment 1

[0038] A rotor winding image detection method that integrates regional distribution characteristics and edge scale angle information, as shown in Figure 1, specifically includes the following steps:

[0039] S1: Perform grayscale preprocessing on the image to be tested, that is, convert the color image into a grayscale image, and then enter the filtering preprocessing operation, that is, use the median filter method to denoise the grayscale image of the image to be tested, and finally perform threshold preprocessing. The processing operation adopts the iterative method to adaptively calculate the threshold value, and performs binarization operation on the filtered gray image with this threshold value, so as to complete the image preprocessing of the winding area, and the image to be tested becomes a binary image, such as figure 2 (a) and figure 2 (b), figure 2 (a) is the preprocessing image of the image to be tested in the present invention. The winding area in the image ...

Embodiment 2

[0045] The difference between this embodiment and Embodiment 1 is that the S2 includes the following steps:

[0046] S21: Calculate the similarity of the spatial distribution characteristics of the contour of the winding area between the image to be tested and the template;

[0047] S22: Relevance search is performed on the template image based on the regional distribution characteristics;

[0048]The template retrieval algorithm based on the distribution characteristics of the contour area needs to perform correlation retrieval on the template image based on the distribution characteristics of the region first, and the distribution correlation between two images (template and image to be tested) can be calculated by the following formula

[0049]

[0050] in: h k (J) is the number of contour sampling points distributed in the J block area, and N is the number of area blocks divided by the distribution descriptor;

[0051] S23: Select the origin, divide and mark the ima...

Embodiment 3

[0055] The difference between this embodiment and the above embodiment is that: the morphological description of the scale and angle information of the contour in S3 is as follows, for any point e on the edge of the contour i (x i ,y i ) and contour centroid O 0 (x 0 ,y 0 ) form the vector r i , the polar radius is defined as It is the scale information, any point e on the edge of the contour i (x i ,y i ) at the angle size can be defined as a vector gradient with the point The included angle θ i , which is the angle information, θ i Calculated as follows

[0056]

[0057] It can be seen that the angle θ i The calculation does not rely on absolute coordinates, but in the vector r i as the relative coordinates of the datum. In this way, the information statistics of the scale and angle based on the centroid are established, and the figure 2 Take the figure (c) as an example, the histogram statistics of the angle and scale of the edge points of the winding...

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Abstract

The invention discloses a rotor winding image detection method fusing region distribution characteristics and edge scale angle information. The method comprises the steps that 1, graying, filtering and threshold preprocessing operation are performed on a to-be-detected image respectively to complete winding region image preprocessing, and the to-be-detected image becomes a binary image; 2, the similarity between spatial distribution characteristics of a winding region contour between the to-be-detected image and a template is calculated to perform template retrieval; 3, through calculation ofrelative angle information of vectors formed by a sampling point on a contour edge of the to-be-detected image and a centroid of the region contour and gradient vectors at the point as well as scale information of the vectors, description of the contour form is realized; and 4, the similarity between angle and scale distribution information of the to-be-detected image and the template is calculated through a Bhattacharyya distance, and then detection of the to-be-detected image is realized. Therefore, the influence of template selection contingency on detection precision is effectively avoided, detection time is shortened, and detection accuracy is improved.

Description

[0001] Field [0002] The invention relates to a digital image processing and visual detection method, and provides a detection method for the winding form of a rotor hook, specifically, a detection method of a rotor winding image that integrates area distribution characteristics and edge scale angle information. Background technique [0003] With the continuous improvement of my country's industrial automation and intelligence level, motors, as key products that can convert electrical energy into mechanical energy, are widely used in large-scale electromechanical equipment in industries, agriculture, etc. In the equipment, the demand for the rotor, which is the core component of the motor rotation system, is also increasing. [0004] During the production process of the rotor, the hooks need to be surrounded by copper wires. Due to the irregular operation and the limitation of the properties of the copper wires, problems such as broken wires and missing hooks are prone to occu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/40G06K9/62
CPCG06T7/0004G06V10/30G06F18/22
Inventor 张小国朱亚旋贾友彬陈刚
Owner SOUTHEAST UNIV
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