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Fire hose defect detection method and system based on computer vision

A computer vision, fire hose technology, applied in manufacturing computing systems, calculations, image analysis and other directions, can solve the problems of misjudgment and missed judgment, affecting the efficiency and accuracy of fire hose detection, to avoid misjudgment and missed judgment, realize The effect of automated defect detection and improved detection efficiency

Active Publication Date: 2022-08-02
南通森田消防装备有限公司
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Problems solved by technology

However, because the texture of the fabric layer of the fire hose is too dense, it will be affected by a large amount of texture information when detecting defects based on pixel differences, resulting in misjudgments and missed judgments, thus affecting the defect detection efficiency and accuracy of the overall fire hose

Method used

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  • Fire hose defect detection method and system based on computer vision
  • Fire hose defect detection method and system based on computer vision

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Embodiment Construction

[0031] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the following describes a computer vision-based fire hose defect detection method and system according to the present invention with reference to the accompanying drawings and preferred embodiments, The specific implementation, structure, features and effects thereof are described in detail as follows. In the following description, different "one embodiment" or "another embodiment" are not necessarily referring to the same embodiment. Furthermore, the particular features, structures, or characteristics in one or more embodiments may be combined in any suitable form.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0033] The specific scheme of a computer vision-based fire ho...

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Abstract

The invention relates to the technical field of fabric defect detection, in particular to a fire hose defect detection method and system based on computer vision. The method determines the abnormal region through the optical flow information. And converting the texture edge in the abnormal region into a Hough space to obtain the form information of the texture edge. Clustering is carried out according to the Hough curve form in the Hough space, and a first cluster is obtained; and obtaining a first defect area according to the number of the abnormal samples in the first cluster. And determining a second defect area according to the abnormal distance between the parallel texture edges corresponding to the first cluster. According to the method, the morphological information of the texture edges is obtained through Hough space conversion, and defect detection is accurately carried out according to the state between the edges.

Description

technical field [0001] The invention relates to the technical field of fabric defect detection, in particular to a method and system for detecting fire hose defects based on computer vision. Background technique [0002] Traditional fire hoses are rubber-lined and linen braided on the outside. At present, the defects of fire hose mainly exist in the fabric layer of the hose, and the fabric layer is required to be woven evenly, the surface is clean, and there is no double warp skipping, double warp breakage, weft skipping and scratches. [0003] It is time-consuming, laborious, and inefficient to manually complete the defect detection of the outer surface water belt fabric layer. Therefore, in the prior art, computer vision technology can be used to determine defects by detecting pixel differences in fabric pictures. However, because the texture of the fabric layer of the fire hose is too dense, it will be affected by a large amount of texture information when detecting defe...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/13G06V10/762
CPCG06T7/0002G06T7/13G06V10/762G06T2207/10016G06T2207/30124Y02P90/30
Inventor 郑尔娟
Owner 南通森田消防装备有限公司
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