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Object surface pattern detection method based on artificial neural network

An artificial neural network and detection method technology, applied in the field of object surface type detection, can solve the problems of easy misjudgment, uncontrollable yield rate of structural objects, poor efficiency, etc.

Pending Publication Date: 2021-04-20
SHENXUN COMP KUNSHAN +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the efficiency of manually detecting whether a structural object has defects is low, and misjudgment is very easy to occur, which will cause the yield rate of the structural object to be uncontrollable

Method used

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  • Object surface pattern detection method based on artificial neural network
  • Object surface pattern detection method based on artificial neural network
  • Object surface pattern detection method based on artificial neural network

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Embodiment Construction

[0019] refer to figure 1 , the object surface type detection method based on the artificial neural network is suitable for an artificial neural network system. The artificial neural network system has a learning phase (ie training) and a prediction phase.

[0020] In the learning stage, the artificial neural network system receives several object images (step S01). Here, these object images are all the surfaces of the same relative position of the same object. Furthermore, the artificial neural network system receives several object images with fixed image capture coordinate parameters.

[0021] Next, the artificial neural network system divides each object image into several image regions (step S02 ), and specifies at least one ROI among the several image regions of each object image (step S03 ). In other words, after an object image is cut into several image regions, the artificial neural network system can designate the corresponding sequence of image regions among the s...

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Abstract

The invention discloses an object surface pattern detection method based on an artificial neural network. The method comprises the following steps: receiving a plurality of object images; dividing each object image into a plurality of image areas; specifying at least one region of interest in a plurality of image regions of each object image; and performing deep learning by using at least one region of interest to establish a prediction model for identifying the surface pattern of an object. By utilizing the object surface pattern detection method based on the artificial neural network, the specific area of the object image can be trained elastically, so that a relatively accurate prediction model is established, and the training time is accelerated.

Description

【Technical field】 [0001] The invention relates to an artificial neural network training system, in particular to an artificial neural network-based object surface type detection method. 【Background technique】 [0002] Various safety protection measures are composed of many small structural objects, such as seat belts. If the strength of these small structural objects is insufficient, the protective effect of safety protection measures can be questioned. [0003] Due to various reasons during the manufacturing process of these structural objects, such as collisions, process errors, mold defects, etc., tiny defects on the surface, such as slots, cracks, bumps, and textures, etc., may occur on the surface. These tiny flaws are not easy to detect. One of the existing defect inspection methods is to manually observe the structural object to be inspected with naked eyes or touch with both hands to determine whether the structural object has defects, such as pits, scratches, colo...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06N3/08G06N3/04
Inventor 蔡昆佑
Owner SHENXUN COMP KUNSHAN
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